JMP Introductory Lab Activities Activity 15: Exploring Categorical Data jmp Data Set: Denim.jmp Summary This data set is the result of an experiment conducted by a company that manufactures blue jeans. Denim fabric naturally contains starch, creating stiffness in the fabric. Most customers find this stiffness uncomfortable, so denim manufacturers subject the fabric to a variety of washing treatments to remove some of the starch and make it feel worn." Although the feel of the fabric is important, the company is also concerned about the strength of the treated fabric, which is measured by a count of the destroyed threads. In this lab you will study which, if any, of the categorical factors is related to the severity of the thread wear of the denim. You'll copy output and summarize your findings in a report (discussion questions and required output are in italics below). The Denim Data Open the file Denim.jmp from the JMP Sample Data directory. The data set contains information on 98 samples of denim, including: The lot number of the fabric. The method used to treat the fabric. The size of the load washed (in lbs.). Whether or not the fabric was sandblasted. The thread wear (an actual count of broken threads between 1 and 10). The thread wear, categorized as low, moderate or severe. The resulting starch content (%). . Data Types The size of the wash load, the thread wear measured and the starch content are numeric variables (they have the continuous modeling type in JMP). The remaining variables are all categorical (these have nominal or ordinal modeling types). Check in the Columns panel to the left of the data table to make sure that Method is shown as a nominal variable (values belong to categories but the order is not important) and Thread Wear is shown as an ordinal variable dl (numeric or character data-values belong to ordered categories). C Objectives Summarize, represent and interpret data on two categorical variables. Use JMP to display a mosaic plot and contingency table for categorical data. Row and column percentages will also be found. E Instructions Activity 15: Exploring Categorical Data e The same command (Analyze > Fit Y by X) is used for both numeric and categorical data. JMP decides which analysis to use based on the modeling types for the variables selected. With two categorical variables (two-way tables), the mosaic plot that JMP displays includes a bar on the far right that represents all of the data. To better understand the mosaic plot, right click on the plot, and select Cell Labeling > Show Percents. These values correspond to the Row % values in the Contingency Table. JMP Introductory Lab Activities Activity 15: Exploring Categorical Data jmp Data Set: Denim.jmp Summary This data set is the result of an experiment conducted by a company that manufactures blue jeans. Denim fabric naturally contains starch, creating stiffness in the fabric. Most customers find this stiffness uncomfortable, so denim manufacturers subject the fabric to a variety of washing treatments to remove some of the starch and make it feel worn." Although the feel of the fabric is important, the company is also concerned about the strength of the treated fabric, which is measured by a count of the destroyed threads. In this lab you will study which, if any, of the categorical factors is related to the severity of the thread wear of the denim. You'll copy output and summarize your findings in a report (discussion questions and required output are in italics below). The Denim Data Open the file Denim.jmp from the JMP Sample Data directory. The data set contains information on 98 samples of denim, including: The lot number of the fabric. The method used to treat the fabric. The size of the load washed (in lbs.). Whether or not the fabric was sandblasted. The thread wear (an actual count of broken threads between 1 and 10). The thread wear, categorized as low, moderate or severe. The resulting starch content (%). . Data Types The size of the wash load, the thread wear measured and the starch content are numeric variables (they have the continuous modeling type in JMP). The remaining variables are all categorical (these have nominal or ordinal modeling types). Check in the Columns panel to the left of the data table to make sure that Method is shown as a nominal variable (values belong to categories but the order is not important) and Thread Wear is shown as an ordinal variable dl (numeric or character data-values belong to ordered categories). C Objectives Summarize, represent and interpret data on two categorical variables. Use JMP to display a mosaic plot and contingency table for categorical data. Row and column percentages will also be found. E Instructions Activity 15: Exploring Categorical Data e The same command (Analyze > Fit Y by X) is used for both numeric and categorical data. JMP decides which analysis to use based on the modeling types for the variables selected. With two categorical variables (two-way tables), the mosaic plot that JMP displays includes a bar on the far right that represents all of the data. To better understand the mosaic plot, right click on the plot, and select Cell Labeling > Show Percents. These values correspond to the Row % values in the Contingency Table