M/microsoft optical mouse-direct-65.txt 65

By practicing this embodiment of the invention, users can improve the speed and efficiency of the tag association process. The invention thus provides a user interface embodied on one or more computer-readable media and executable on a computer for the selection of a set of metadata tags from a superset of metadata tags, wherein said superset of tags comprises a hierarchal structure of tag nodes with one or more nested tag node subsets, said user interface comprising:.

In another embodiment of the invention, a method is provided for the association of one or more choices from a structured list of choices with a computer representation of an item. Accordingly, the invention provides a computer readable medium encoded with computer-executable instructions which, when executed by a computer, perform a method of associating a representation of an item with one or more choices, wherein said representation of said item is encoded on a computer readable medium, and wherein the method comprises:.

Broadly speaking, the method of the present invention involves. In another embodiment, the present invention provides a methods for storing, and presenting metadata vocabularies which include the descriptions of tags so possible adopters will know the exact purpose of the tags in the tag vocabulary, and guidance for the creation of new tags to supplement the existing tags.

In another embodiment, the present invention provides guidance for the application of a specific tag in the broader context of the tag vocabulary. A further understanding of the functional and advantageous aspects of the invention can be realized by reference to the following detailed description and drawings. The embodiments of the present invention are described with reference to the attached figures, wherein:. Generally speaking, the systems described herein are directed to a computer readable medium encoded with computer-executable instructions which, when executed by a processor, perform a method of associating a file with one or more metadata tags.

As required, embodiments of the present invention are disclosed herein. However, the disclosed embodiments are merely exemplary, and it should be understood that the invention may be embodied in many various and alternative forms. The Figures are not to scale and some features may be exaggerated or minimized to show details of particular elements while related elements may have been eliminated to prevent obscuring novel aspects.

Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting but merely as a basis for the claims and as a representative basis for teaching one skilled in the art to variously employ the present invention. For purposes of teaching and not limitation, the illustrated embodiments are directed to a computer readable medium encoded with computer-executable instructions which, when executed by a processor, perform a method of associating a file with one or more metadata tags.

These terms are not to be interpreted to exclude the presence of other features, steps or components. For example, metadata items may include but are not limited to title information, artist information, program content information such as starting and ending times and dates for broadcast program content , expiration date information, hyperlinks to websites, file size information, format information, photographs, graphics, descriptive text, and the like.

Furthermore, data files can themselves be metadata for a real world object, for example, the photograph of a collectible the characteristics applied to the photo do not relate to the photo itself, but to the subject of the photo or the sound of a musical instrument the sound file is representative of the musical instrument, and is not itself a valuable data file.

All of these types of metadata require management and, to date, no prior art comprehensive tool set exists that supports these diverse metadata applications. Generally speaking, files will have metadata tags that are relevant to a number of characteristics of the file and the overall file set, including, but not limited to, the file's technical aspects format, bytes used, date of creation , the workflow in which the file participates creator, owner, publisher, date of publication, copyright information, etc and the subject matter of the file the nature of the sound of an audio file, be it music or a sound-effect, the subject of a photograph or video clip, the abstract of a lengthy text document, excerpted particulars of invoices or other data-interchange format files.

The present invention provides an improved method of classifying an item based on selecting one or more descriptive tags from a structured set of tags. The structured set of tags is provided in a hierarchal format. Unlike prior art classification methods, the present invention provides a method that is more user-friendly by only presenting, at a given time during the classification process, a limited number of tag choices that correspond to a given level within the hierarchy.

The method also advantageously improves the user experience by guiding the user through a progression of such choices. In a preferred embodiment, the invention provides a method for applying metadata tags to a file, including, but not limited to, media files such as digital photos, music, and videos.

The invention provides several improvements over prior art metadata methods, including a reduction in the precision required for most of the clicks in a tree or other tag representation, and a reduction in the total number of clicks required to tag a file.

An exemplary operating environment for implementing the present invention is described below with reference to FIG. Computing device is but one example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the invention. Neither should the computing-environment be interpreted as having any dependency or requirement relating to any one or combination of components illustrated. With reference to FIG.

Bus represents what may be one or more busses such as an address bus, data bus, or combination thereof. Although the various blocks of FIG. Also, processors have memory. It should be noted that the diagram of FIG. Computing device typically includes a variety of computer-readable media.

The memory may be removable, nonremovable, or a combination thereof. Exemplary hardware devices include solid-state memory, hard drives, optical-disc drives, etc. Presentation component s present data indications to a user or other device. Exemplary presentation components include a display device, speaker, printing component, vibrating component, etc. Illustrative components include a microphone, joystick, game pad, satellite dish, scanner, printer, wireless device, etc. In certain preferred embodiments of the invention, a computing device executes computer-executable instructions, which represent any signal processing methods or stored instructions.

Generally, computer-executable instructions are implemented as software components according to well-known practices for component-based software development, and encoded in computer-readable media such as computer-readable media.

Computer programs may be combined or distributed in various ways. Computer-executable instructions, however, are not limited to implementation by any specific embodiments of computer programs, and in other instances may be implemented by, or executed in, hardware, software, firmware, or any combination thereof. Generally speaking, the present invention may be implemented on a computing device such as the device shown in FIG.

A user interface, as used herein, is a physical or logical element that defines the way a user interacts with a particular application or device, such as client-side operating environment. Generally, presentation tools are used to receive input from, or provide output to, a user. An example of a physical presentation tool is a display such as a monitor device.

An example of a logical presentation tool is a data organization technique such as a window, a menu, or a layout thereof. Controls facilitate the receipt of input from a user.

An example of a physical control is an input device such as a remote control, a display, a mouse, a pen, a stylus, a microphone, a keyboard, a trackball, or a scanning device. An example of a logical control is a data organization technique via which a user may issue commands. It will be appreciated that the same physical device or logical construct may function as an interface for both inputs to, and outputs from, a user.

Computer-readable media, as described herein, represents any number and combination of local or remote devices, in any form, now known or later developed, capable of recording, storing, or transmitting computer-readable data, such as computer-executable instructions or data sets.

Computer-readable media may also include transmission media and data associated therewith. As noted above, the invention is described as implemented with computer or machine-useable instructions, including computer-executable instructions such as program modules, being executed by a computer or other machine, such as personal electronic devices.

Generally, program modules including routines, programs, objects, components, data structures, etc. The invention may be practiced in a variety of system configurations, including hand-held devices, consumer electronics, general-purpose computers, more specialty computing devices, etc.

Examples of personal electronic devices include but are not limited to mobile phones, personal digital assistants, personal computers, media players, televisions, set-top boxes, hard-drive storage devices, video cameras, DVD players, cable modems, local media gateways, and devices temporarily or permanently mounted in transportation equipment such as planes, or trains, or wheeled vehicles.

The preceding operating environment for implementing the present invention is provided merely as an example. The invention may also be practiced in distributed computing environments where tasks are performed by remote-processing devices that are linked through a communications network. For example, the invention may be enabled in a client-server architecture, or may be provided in a hosted or in a software-as-a-service model. The invention may be implemented with a wide range of computing devices, environments or systems that communicate over a network.

The invention may be implemented with devices in communication other devices, which may include but are not limited to personal digital devices, remote servers, computers or other processing devices. In a preferred embodiment of the invention, the user is guided through a tagging process.

A file to be tagged with metadata tags is presented to the user or selected by the user in a user interface. One or more metadata tags may then be applied to the file according to the following method. As described above, the metadata tags reside in a hierarchal structured set. The set comprises primary tag nodes, which form the first subset of tag nodes within the hierarchal structure, intermediate nodes, which are all non-primary nodes to which additional tag nodes below, and leaf tag nodes, that terminate the hierarchal structure.

Unlike prior art metadata tagging methods and user interfaces, the present invention does not simply present the entire hierarchal structure to the user, but instead assists the user in the selection of appropriate metadata tags through a guided process. In a preferred embodiment, one subset of tag nodes is active at any given time during the tagging process. In a preferred embodiment of the invention, a user interface displays to the user a first subset of primary tag nodes, which generally represent high-level categories.

The user selects a primary node to activate, which causes the user interface to display the subset of tag nodes that are in the next level of the hierarchal structure; in other words, the selection of the primary node causes the user interface to display the tag nodes belonging to the primary tag node.

The tag nodes may include intermediate tag nodes, leaf tag nodes, or a combination of the two. The user selects an intermediate tag node, which in turn causes the next level of tag nodes to be displayed, i. According to a preferred method of the invention, deeper tag node subsets within the hierarchal structure of the set of tabs are sequentially presented to the user until a leaf tag node is selected. Upon the selection of an appropriate leaf tag node, the subset of primary tag nodes is again presented to the user, and the process is repeated for the additional primary tag nodes.

The above method is shown in FIG. In a first step of the illustrated method, a file is selected to be associated with one or more metadata tags. Step , and further steps in which the method includes the interaction with a user, are preferably executed via a user interface. The file may be selected by the user, or may be provided by an automated search of a computing environment resulting in a list of candidate files.

A set of tags, provided in a hierarchal format, is used for the association of the file with metadata. The set of tags, arranged as tag nodes within the hierarchal structure, may be a predefined set of tags, or the set may be imported from another user of third party source. The set may further comprise a combination of user-defined tag nodes and third-party tag nodes. The tag set may be loaded from a computer readable media that can include, but is not limited to, a user's hard drive, a portable media source, or a networked source such as a remote server.

The tag set is preferably provided and stored as a data structure preserving the hierarchal format of the tag nodes contained therein. As shown in step of the method, an active tag node is first identified as a primary tag nodes.

This primary node is a node from the first level of nodes in a hierarchal format, eg. Subsequently, in step , the tag nodes subset belonging to the active tag node are presented to the user for selection.

The primary tag node subset likely does not contain leaf tag nodes and is instead made up of intermediate nodes having tag node subsets. In step , the user selects an intermediate tag node assuming no leaf tag nodes are present and in step , the tag node subset belonging to the selected intermediate tag node becomes the active tag node subset.

Step is subsequently repeated, this time displaying the tag node subset belonging to the new active tag node. If a leaf tag node belongs to the new active tag node and the user selects the leaf tag node in step , then the selected tag node is associated with the file in step , and then if in step there are additional primary tag nodes that have not yet been identified, then a previously unactivated primary tag node is activated as the active tag node in step , and step is repeated.

If, on the other had, if the active tag node subset had contained an intermediate tag node that was selected by the user in step , then as before, the tag node subset belonging to the selected intermediate tag node would become the active tag node subset, and step would be repeated, displaying the new active tag node subset.

The above process continues until it is determined in step that all primary tag nodes have been activated, i. The collection of tag nodes associated by the user by the selection of leaf tag nodes if any is subsequently associated with the selected file in step In a preferred embodiment, the metadata is embedded in the file.

In a preferred embodiment, the user may terminate the tag selection process at any time during the aforementioned steps, for example, by the selection or actuation of a user interface button or context menu item. A file is selected in step In step of the method, a primary tag node is activated by the user as the active tag node.

In step , the tag node subset belonging to the active tag node is presented to the user for selection. In step , if the user selects an intermediate tag node and in step , the tag node subset belonging to the selected intermediate tag node becomes the active tag node subset, and step is repeated, this time displaying the tag node subset belonging to the new active tag node. If a leaf tag node is selected in step , then the selected tag node is associated with the file in step , and if all primary tag nodes have not yet been activated in step , the user again selects a primary tag node as the active tag node in step As in FIG.

The preceding embodiments, and variations thereof, are henceforth described with reference to an embodiment in which a user selects metadata tags via a user interface that displays tag nodes within a tree structure.

Those skilled in the art will readily appreciate that this specific embodiment of the methods of the invention is a non-limiting example that can by adapted to other related methods and presentation formats. To further illustrate this compatibility and generalization of the invention to other methods, further examples are provided later sections of this disclosure in which the tag nodes are presented in column display format and in a multi-pane window format with selectable tabs and buttons.

The following example provides an embodiment in which a method of the invention is adapted to a user interface in which the hierarchal tag structure is presented in a tree format.

With reference to the FIGS. Additionally, the top-level nodes exposed are each queued to be visited, as described below. See FIG. The user now looks at the photo, and decides which people are present and worthy of being encoded into the metadata of the photo.

The more interesting case is where, again with reference to FIG. The resulting appearance can be seen in FIG. Another option is that the tag that was applied remains visible without its siblings, as in FIG.

The optional display of existing and freshly applied metadata is shown, in the following continuation of this example. The above description encapsulates the main benefit of the TAP mode interface. In the following paragraphs the generalizations and expansions on this procedure are described, for cases where the user needs to supply or edit additional metadata.

The text is a larger target and more intuitive than an icon, since the user knows exactly which choice he or she wants to make and clicks directly on the text word. Picture icons could also be used, in tree form, to provide an even larger target for clicking, an embodiment that would be useful for making the tagging process accessible to children. The user's attention need not leave the text or image representing the keyword they wish to apply, as would be required to click a checkbox or other user interface component distinct from the text itself: the user need just move the mouse to where their eyes are already looking.

It is important to note that as in FIG. The important feature to be noted in hiding intervening nodes is the dual benefit of simplifying the user interface and bringing nodes closer to the mouse pointer the above-mentioned procedure is that once a decision is made, the distracting options that were not chosen are hidden from view. This would hide the individual attractions and instead show the parts of Toronto again. This would cause the tree, as pictured in FIG. Thus the user has control of what in the tree is visible, but in the context not of exploring the tree, but of applying metadata.

Additional capabilities related to editing metadata may readily be incorporated into the TAP. The nodes representing already-embedded metadata are visible in the tree, and by clicking them the user can direct that they be removed from the file. In the case of a multiselection, the user may have control over whether all selected files' metadata are shown or just the metadata related to a particular file considered to be the focused file. Tooltips can also be provided which allow the user to determine the status and properties of a node already present in the metadata, to augment the information provided by the icons, and jog the user's memory if he forgets the meanings of the icons.

In addition to the above tag assignment procedure implementation, the present invention provides an additional method and user interface for improving the ergonomics of a hierarchal-based control for applying metadata.

First, by implementation of a mode activated by a toolbar button or menu command, or by use of a context menu option, the user can change the function of clicks on nodes to be in the nature of configuration, rather than tagging. In the case of FIG. Nodes not having their checkbox checked will show in configuration mode, and perhaps at user option when found in existing metadata in the selected files, but will not be shown in the tree, and will not be expanded and visited during the TAP.

Appropriate use of three-state checkboxes can be used to additionally inform the user that a certain collapsed node has descendant nodes some of which are checked and some of which are unchecked. Different industry standard methods can be used to indicate the three choices, including special icons, a gray checkmark or perhaps a shading of the checkbox. These choices are familiar to a programmer of ordinary skill in user interface development. This can be achieved by colouring the text on the parent node, or by modifying the icon on the parent node.

Note that while in FIG. Note that in FIG. It could be configured to activate the checkbox on all the direct children, or perhaps recursively check all the descendant nodes in all descendant branches, or to uncheck children or descendants that are already checked. For example, clicking on a partly populated checkbox can result in unchecking of all the checked child nodes.

An undo capability allows the user to reverse the effect of the checkbox operation, in case it was not as intended. It's also advantageous to save several different configurations of the checkboxes, for use in different kinds of file tagging operations.

For instance, if tagging photos of a wedding you need different top-level choices than for photos of a sporting event. So by allowing the user to suppress display of certain nodes in the tree based on knowledge of the general subject matter in the file set, it's possible to simplify the visual appearance of the tree and improve the efficiency and lower the effort required to apply tags.

To save the configuration of checkboxes in the tree at any time, it would suffice to name the parent nodes in a text based list, and mention only those nodes which are checked off fully. There's no need to name the sub-nodes which are also checked off, but it's an option available to the programmer. Optionally, the settings could be stored in one large file similar to an. There are additional features for simplifying this process, such as an additional user interface for selecting tagets, an example is provided in FIG.

However, for a modification or retrofit of a tool such as Windows Photo Gallery included with some versions of the Windows Vista operating system , these improvements are not essential for the realization of the major advantages of the TAP. Further description of the capabilities of the tagset chooser can serve to make the capabilities and function of the tagset chooser clear, in relation to applicability to trees, even to a programmer unfamiliar with the TAP interface, so it will be described in detail here.

The tagset chooser pane can be provided an area having buttons labeled with the names of saved tagsets, and provisions for adding a new tagsets, or saving the existing configuration of checkboxes into a new tagset. In the process of saving a configuration the user can be prompted to supply a name for the configuration and a filename for storing it.

One additional feature that is very valuable in the tagset chooser is the ability to select more than one tagset button at once.

A non-control click of a non-pressed button may unclicks the existing buttons and clicks the new button. In this way, the user can make many very small tagsets and activate multiple tagsets to create task-specific composite tagsets from smaller, easier-to-manage tagsets.

Another option for implementation of multiple tagset selection is to make a click on a single tagset button a simple toggle for that specific tagset. This alleviates the requirement to control-click additional buttons, further reducing the need to interact with the keyboard while tagging and configuring.

By including additional tagsets using procedures as the above methods describe, the effect is to bring in additional checkmarks into the tree. The union of all the sets of checked nodes is used in the tree. Another requirement when tagging structured metadata is that in some cases, more than one sub-branch of the tree needs to be visited and used. Consider now the example where a photo depicts a coworker and a relative.

In FIG. By use of the control key, held during the mouse-click on the node, the result can achieved with a minimum of additional operations. The control key is held while all the parallel node choices are pressed, then released once this is done. On release of control, the first oldest control clicked node is expanded because it will be the next queued node.

However, a difference from the standard TAP described above is that the other control-clicked nodes are not hidden in the tree, but remain as collapsed siblings to the expanded node. This process can be repeated at lower levels, resulting in a tree with some partially populated nodes and some top level nodes still fully collapsed. The requirement is that the control key should continue to be held down from the point before the first button is clicked until after the second button is clicked.

The same principle applies. When the control key is released, because none of the pressed nodes had sub-nodes, their branches are finished.

The next node queued for inclusion in the TAP is activated. As shown in FIG. The resulting tree is shown in FIG. One intuitive way of indicating this is to start the TAP with the 4 top-level nodes indicated as if they had just been control clicked, and the initial expansion of the people node corresponds to the release of control. In the case of pressing a checked node, the result is always to remove the check but not change the activated node.

If one is found, use it. If not, continue up to the next ancestor. Another action which is common in the use of a nested vocabulary is that the user may see a word that needs to be added to the keyword tree because it is not yet present under the appropriate parent node. In some cases, the user may type a name that is already in the keyword tree but not currently being shown in the tree the node was not explicitly chosen to be included in the tagset.

In this case, after a few characters have been typed, and those characters match the first few characters of an existing keyword, the existing keyword can be offered to the user, in a method similar to automatic word completion utilities on text editors. Nodes added can be created in place, by inserting a new node and having the text of the node label being actively edited in place, or by popping up a prompt with a text entry field, then adding the new node to the tree, under the activated node, in the proper location.

In order to facilitate the addition of new nodes to the tree, during TAP mode, it is necessary to render them in the tree even though they would otherwise not be shown, by virtue of them being recently created, where the duration is until the next redraw of the tree due to the display of a new activated node. The nodes are not hidden either: they remain visible until their parent is collapsed, so the user has a chance to either enter more nodes under the same activated node, or to control click nodes to apply both the newly created node and some nodes already present and displayed in the tree.

Specific keys that don't create characters used in keywords can be used to specify actions following completion of text entry for a single tag.

There are some additional features that can be applied to a tree showing metadata, that come into play when the image is accessed for a second time, after tags have already been applied. One option is to display the existing metadata in the tree as well as the nodes available for use in the TAP. The extra nodes are shown with an icon indicating they are in fact already in the metadata, but in the case where they happen to have descendant nodes they will not actually be visited as expandable nodes in the TAP.

Paths of checked-off parent nodes that represent embedded metadata can remain expanded above the current node, so that it is possible by looking in the tree to see what metadata is already present in the file, without having to navigate see FIG. These will scroll out of view as the tree control is scrolled. This is the default display method. You added Microsoft Classic IntelliMouse to your wish list.

You can share this list with others. Continue shopping View wish list. The fan-favourite mouse of yore has been transformed with modern improvements like more precise tracking and reliable button action while maintaining the c.

Check your eligibility. Overview Tech specs. Previous Next. A legend reborn Inspired by the Microsoft Intellimouse 3. It has all the features you loved from the original—from customizable 1 buttons and classic ergonomic look and feel to the wired-USB connection.

And with more precise tracking, buttons that feel more reliable, and a distinctive, modern white tail light, this new take on a classic mouse keeps up with your hectic workload. Click with ease Quickly and efficiently complete your most common tasks with two customizable 2 thumb buttons and a middle click.

Exceptional fit The ergonomic design fits your hand comfortably for hours of pain-free navigation and easy maneuvering. Trusted connection Plug in the fast, wired-USB connector without waiting for Bluetooth to pair or searching for a dongle. Shop other products. Skip Shop other products Previous slide Next slide. Why shop at Microsoft Store. Fast, free shipping Get your order in days with no minimum purchase required. See shipping details.

Free returns Return almost any product in like-new condition in its original packaging within 30 days. See returns details. Instant software downloads Install most apps and software, like Microsoft , Windows, and Xbox games, via digital download. Learn about digital downloads. Get one-on-one support any time via chat or phone, or find answers fast with common FAQs. Get support. Not available on Windows 10 S. You must accept License Terms for software, and download at: microsoft. This procedure uses a slightly different formula for the CI than presented in class, and the results of the two versions of the formula may differ slightly.

There is also a 'binom. For the following syntax, the underlying data set includes the subjects from both samples, with one variable indicating the dependent variable the outcome variable and another variable indicating which group a subject is in. For the usual pooled-variance version of the t-test:. Two Sample t-test. The t-statistic and p-value are discussed under Section 2. Note that the output gives the means for each of the two groups being compared, but not the standard deviations or sample sizes.

This additional information can be obtained using the tapply function as described in Section 7 in this example, tapply agewalk,group,sd will give standard deviations, table group will give n's. To calculate the confidence interval for the difference in means using the unequal variance formula:.

Welch Two Sample t-test. Again, it's good to check the title Welch Two Sample t-test and degrees of freedom which often take on decimal values for the unequal variance version of the t-test to be sure R is using the unequal variance formula for the confidence interval and t-test.

In this situation, we need to specify the two data vectors representing the two variables to be compared. The following example compares the means of a pre-test score score1 and a post-test score score2 from a sample of 5 subjects. Generally standard deviations and sample size would also be reported, which can be obtained from the sd and length functions.

Paired t-test. Note that the t. Generally, standard deviations are reported as part of the data summary for a comparison of means, and these standard deviations can be found using the ' sd ' command. The table command is used to find the number of infants walking by 1 year in each study group, and the proportion walking can be calculated from these frequencies. In prop. Chi-squared approximation may be incorrect.

The procedure also gives the results of a chi-square test comparing the two proportions see Section 2. For this example, The difference in these two proportions is Epidemiologic analyses are available through 'epitools', an add-on package to R. To use the epitools functions, you must first do a one-time installation. In R, click on the 'Packages' menu, then 'Install Package s ', then select a download site from the US , then select the epitools package. This will install the add-on package onto your computer.

To use the package, you must also load it into R: click on the 'Packages' menu, then 'Load Package', then select epitools.

While you only need to install the package once onto your computer, you will need to load the package into R each time you want to use it. The data layout matters for calculating RRs. For the riskratio function from epitools, data should be set up in the following format:.

The riskratio command calculates the RR of disease for those in the exposed group relative to the control group. Using the Age at Walking example, I'll find the relative risk of being a late walker walking at 12 months or older for those in the non-exercise group compared to those in the exercise group. With the variables defined in this manner, the table should be oriented correctly for the RR of interest.

Predictor 0 1 Total. Predictor estimate lower upper. Predictor midp. In chisq. The RR here is 3. There are several versions of a CI for a relative risk, and using ' riskratio. R will choose the appropriate version of the CI if 'riskratio ' is specified.

Cell counts from a 2x2 table or larger tables can also be entered directly into R for analysis RR, OR, or chi-square analysis. For example, the following table presents data on adverse side effects for patients undergoing robot-assisted vs. The rate of side effects was 2. Table orientation matters for the RR see Section 2. R treats data entered using the column command c as columns of numbers, so data must be entered by column — counts for the first column followed by counts for the second column.

Predictor Disease1 Disease2 Total. Exposed1 Exposed2 Total Exposed1 1. Exposed2 2. Exposed2 1. Those given robot-assisted surgery had 2. The epitools add-on package also has a function to calculate odds ratios and confidence intervals for odds ratios. You must first load the epitools package into R see Section 2. Orientation of the table matters when calculating the OR, and the orientation described above for the relative risk also applies for the odds ratio.

The oddsratio. The ' oddsratio. The one-sample t-test compares the mean from one sample to some hypothesized value. For input, we need to specify the variable vector that we want to test, and the hypothesized mean value. To test whether the mean age at walking is equal to 12 months for the infants in our age of first walking example:. R performs a two-tailed test, as indicated by the two-tailed language in the alternative hypothesis.

The p-value here is given in scientific notation, and the 'e' indicates that the decimal place should be moved 5 spaces to the left; 3. If there is a significant difference between the sample mean and the hypothesized mean, the confidence interval will not contain the hypothesized value. This information can be obtained using the sd function and the length function sd agewalk and length agewalk for this example — although care is needed with the length command when there are missing values.

To perform the independent samples t-test, we need to specify the object representing the dependent variable and the object representing the group information.

R reports a two-tailed p-value, as indicated by the two-tailed phrasing of the alternative hypothesis. Again, it's good to check the title Welch Two Sample t-test and degrees of freedom which often take on decimal values for the unequal variance version of the t-test to be sure R is performing the unequal variance version of the two sample t-test.

As discussed above, standard deviations and sample sizes are also usually given as part of the summary for a two-sample t-test. The following example compares the means of a pre-test score variable score1 and a post-test score variable score2 from a sample of 5 subjects.

By default, R will perform a two-tailed test. The variable 'walkby12' that takes on the value of 1 for infants who walked by 1 year of age, and 0 for infants who did not start walking until after they were a year old. Note that the CI here does not contain the null value of 0. There is also a ' binom.

The z-test comparing two proportions is equivalent to the chi-square test of independence, and the prop. The p-value from the z-test for two proportions is equal to the p-value from the chi-square test, and the z-statistic is equal to the square root of the chi-square statistic in this situation.

Since the p-value is less than the conventional 0. The procedure gives a chi-square statistic which is equal to the square of the z-statistic. Here the z-statistic would be the square root of 7.

The procedure also gives the results of a confidence interval for the difference between the two proportions see section 2. As an example, suppose we want to compare the mean days to healing for 5 different treatments for fever blisters.

So I generally save the 'results' of the ANOVA as an object, and then ask for different parts of the output through different commands. If the grouping variable is a numeric variable, you can declare it to be categorical using the factor function.

We can now request different summary results about the analysis using the results of this analysis. To see the means for the study groups:. Tables of means. The select if command or the tapply function can be used to get standard deviations and sample sizes for each group, as described in Section 5b: Finding means and standard deviations for subgroups.

TreatmentF 4 Residuals 25 Given the overall ANOVA shows significance, we can request pairwise comparisons using Tukey's multiple comparison procedure:. Tukey multiple comparisons of means. The following gives the syntax needed to calculate a chi-square goodness-of-fit test from a set of tabled frequencies. As an example, 45 subjects are asked which of 3 screening tests they prefer; 10 subjects prefer Test A, 15 prefer test B, and 20 prefer Test C.

The data:. To analyze these data in R, first create an object arbitrarily named 'obsfreq' in the example that contains the observed frequencies. Second, we create an object that contains the expected probabilities under the null arbitrarily named 'nullprobs'; the third probability was rounded to.

Third, we compare the observed frequencies to the expected probabilities through the chisq. Chi-squared test for given probabilities.

We can first use the 'table ' function to get the observed counts for the underlying frequency table:. In group 2, The 'prop. The ' prop. Had we indicated '2' in the above example, R would have calculated proportions within sex, giving the proportions in groups 1 and 2 for males, and the proportions within groups 1 and 2 for females. Specifying the orientation for the prop. R can be used as a calculator to find these proportions directly:. The chisq. Pearson's Chi-squared test.

R gives a two-tailed p-value. Note that the title for the output, 'Pearson's Chi-squared test' indicates that these results are for the uncorrected not Yates' adjusted chi-square test. R can also perform a chi-square test on frequencies from a contingency table.

For example, suppose we want to compare percent of subjects testing positive on a marker for an exposure across three groups:. First, we create an object 'obsfreq' in the example containing the observed frequencies from the observed table. I printed the object as a check that it was created correctly:. The ' chisq. The usual chi-square test is appropriate for large sample sizes.

For 2x2 tables with small samples an expected frequency less than 5 , the usual chi-square test exaggerates significance, and Fisher's exact test is generally considered to be a more appropriate procedure. The fisher. Fisher's Exact Test for Count Data. R gives the two-tailed p-value, as indicated by the wording of the alternative hypothesis. Since Fisher's test is usually used for small sample situations, the CI for the odds ratio includes a correction for small sample sizes.

For the Age at Walking example, I categorized age at walking as early walking under 12 months, coded 0 and late walking 12 months or older, coded 1. To find the relative risk for late walking, for kids in Group 2 vs.

There are several versions of a CI for a relative risk, and using 'riskratio. You must first load the epitools package into R see Section 16d. Group 1 in the Age at Walking example:. The wilcox. With samples less than 50 and no ties, R calculates an exact p-value, otherwise R uses a normal approximation with a correction factor to calculate a p-value. To perform a Wilcoxon rank sum test, data from the two independent groups must be represented by two data vectors.

The following commands create separate data vectors for lactate for subjects in the two study groups see Section 7 for the subset command; I printed the two data vectors as a check :. The following performs the Wilcoxon rank sum test. Note that the wilcox. Wilcoxon rank sum test. Another way to create separate data vectors for the sga and control infants would be to use the 'select if' command rather than the subset command.

This avoids creating multiple versions of the data set :. The paired data must be represented by two data vectors with the same number of subjects. In this example, the prescores and postscores variables represent paired test results before and after an intervention. The summary function would give the range and interquartile range in addition to the median. Wilcoxon signed rank test with continuity correction.