**New StatCrunch Commands for Sullivan Statistics**

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**New StatCrunch Technology Step-by-Step**

**Section 1.3 Obtaining a Simple Random Sample**

**1. **Select **Data**, highlight **Simulate**, then highlight **Discrete Uniform**. **2. **Fill in the window with the appropriate values. To obtain a simple random sample for the situation in Example 2, enter the values shown in the figure below. The reason we generate 10 rows of data (instead of 5) is in case any of the random numbers repeat. Click Compute! and the random numbers will appear in the spreadsheet. *Note*: You could also select the single dynamic seed radio button to set the seed.

**Section 2.1 Organizing Qualitative Data**

**Frequency or Relative Frequency Distributions from Raw Data**

**1. **If necessary, enter the raw data into the spreadsheet. Name the column variable. **2. **Select **Stat**, highlight **Tables**, and select **Frequency. ****3. **Click on the variable you wish to summarize. Click the Type of table you want. If you want both Frequency and Relative Frequency, highlight Frequency, then press Shift and select Relative frequency. Click Compute!.

**Bar Graphs from Summarized Data**

**1. **If necessary, enter the summarized data into the spreadsheet. Name the variable and frequency (or relative frequency) columns. **2. ** Select **Graph**, highlight **Bar Plot**, then highlight **with summary**.**3. **Select the "Categories in:" variable and "Counts in:" variable. Choose the type of bar graph (frequency or relative frequency). Enter labels for the X-axis and Y-axis. Enter a title for the graph. Click Compute!.

**Bar Graphs from Raw Data**

**1. **If necessary, enter the raw data into the spreadsheet. Name the column variable. **2. ** Select **Graph**, highlight **Bar Plot**, then highlight **with data**.**3. **Click on the column name of the variable you wish to summarize. Leave the grouping option as "Split bars". Choose the type of bar graph (frequency or relative frequency). Enter labels for the X-axis and Y-axis. Enter a title for the graph. Click Compute!.

**Side-by-Side Bar Graphs from Summarized Data**

**1. **If necessary, enter the summarized data into the spreadsheet. Name the columns. **2. **Select **Graph**, highlight **Chart**, then highlight **columns**. ** 3. **Select the column variables that contain the frequency or relative frequency of each category. Select the column of the variable that has the row labels. Choose the display you would like (vertical or horizontal split bars). Click Compute!.

**Pie Chart from Summarized Data**

**1. **If necessary, enter the raw data into the spreadsheet. Name the column variable.**2. **Select **Graph**, highlight **Pie Chart**, then highlight **with summary**. **3. **Select the "Categories in:" variable and "Counts in:" variable. Choose the display you would like. Enter a title for the graph. Click Compute!.

**Pie Chart from Raw Data**

**1. **If necessary, enter the raw data into the spreadsheet. Name the column variable.**2. **Select **Graph**, highlight **Pie Chart**, then highlight **with data**.**3. **Click on the column name of the variable you wish to summarize. Choose the display you would like. Enter a title for the graph. Click Compute!.

** **

**Section 2.2 Organizing Quantitative Data: The Popular Displays**

**Histograms**

**1. **If necessary, enter the raw data into the spreadsheet. Name the column variable.**2. ** Select **Graph** and highlight **Histogram**. **3. **Click on the variable you wish to summarize. Choose the type of histogram (frequency or relative frequency). You have the option of choosing a lower class limit for the first class by entering a value in the cell marked "Start bins at:" You have the option of choosing a class width by entering a value in the cell marked "Binwidth:" Enter labels for the X-axis and Y-axis. Enter a title for the graph. Click Compute!.

**Stem-and-Leaf Plots**

**1. **If necessary, enter the raw data into the spreadsheet. Name the column variable.**2. **Select **Graph** and highlight **Stem and Leaf**. **3. **Click on the variable you wish to summarize. Select None for outlier trimming. Click Compute!.

**Dot Plots**

**1. **If necessary, enter the raw data into the spreadsheet. Name the column variable.**2. **Select **Graph** and highlight **Dotplot**.**3. **Click on the variable you wish to summarize. Enter labels for the X-axis and Y-axis. Enter a title for the graph. Click Compute!.

**Section 3.1 Measures of Central Tendency**

**1. **If necessary, enter the raw data into the spreadsheet. Name the column variable.**2. ** Select **Stat**, highlight **Summary Stats, **and select **Columns**. **3. **Click on the variable you wish to summarize. Deselect any statistics you do not wish to compute by clicking on the statistic. If you wish to compute certain statistics hold down the Control (Ctrl) key when selecting the statistic. Click Compute!.

**Section 3.2 Measures of Dispersion**

Use the same steps followed to obtain the measures of central tendency.

**Section 3.3 Measures of Central Tendency & Dispersion from Grouped Data**

**1. **If necessary, enter the summarized data into the spreadsheet. Name the columns. **2. **Select **Stat**, highlight **Summary Stats**, and select **Grouped/Binned data**. ** 3. **Choose the column that contains the class under the "Bins in:" drop-down menu. Choose the column that contains the frequencies in the "Counts in:" drop-down menu. Select the "Consecutive lower limits" radio button for defining the midpoints. Click Compute!.

**Section 3.4 Measures of Position and Outliers**

**Determining Quartiles**

Follow the same steps followed to obtain the measures of central tendency.

**Section 3.5 The Five-Number Summary and Boxplots**

**Drawing Boxplots**

**1. **If necessary, enter the raw data into the spreadsheet. Name the column variable.**2. **Select **Graph **and highlight **Boxplot**. **3. **Click on the variable whose boxplot you want to draw. If you wish to draw side-by-side boxplots, hold the Control key down while clicking the variable. Check the boxes "Use fences to identify outliers" and "Draw boxes horizontally". Enter label for the X-axis. Enter a title for the graph. Click Compute!.

**Section 4.1 Scatter Diagrams and Correlation**

**Scatter Diagrams**

**1. **If necessary, enter the explanatory variable in column var1 and the response variable in column var2. Name each column variable. ** 2. **Select

**Graph**and highlight

**Scatter Plot**.

**3.**Choose the explanatory variable for the X column and the response variable for the Y column. Enter the labels for the X-axis and Y-axis. Enter a title for the graph. Click Compute!.

**Correlation Coefficient**

**1. **If necessary, enter the explanatory variable in column var1 and the response variable in column var2. Name each column variable.**2. **Select **Stat**, highlight **Summary Stats**, and select **Correlation**. **3. **Click on the variables whose correlation you wish to determine. Click Compute!.

**Section 4.2 Least-Squares Regression**

**Determining the Least-Squares Regression Line**

**1. **If necessary, enter the explanatory variable in column var1 and the response variable in column var2. Name each column variable.**2. **Select **Stat**, highlight **Regression**, and select **Simple Linear**. **3. **Choose the explanatory variable for the X variable and the response variable for the Y variable. If you want, enter a value of the explanatory variable to Predict Y for X. If you want the least-squares regression line drawn on the scatter diagram, highlight Fitted line plot under Graphs. Click Compute!.

**Section 4.3 Diagnostics on the Least-Squares Regression Line**

**The Coefficient of Determination, R^{2}**

Follow the same steps used to obtain the least-squares regression line. The coefficient of determination is given as part of the output (R-sq).

**Residual Plots**

**1. **If necessary, enter the explanatory variable in column var1 and the response variable in column var2. Name each column variable.**2. **Select **Stat**, highlight **Regression**, and select **Simple Linear**. **3. **Choose the explanatory variable for the X variable and the response variable for the Y variable. Under Graphs, select Residuals vs. X-values. Click Compute!.

**Section 4.4 Contingency Tables and Association**

**Contingency Tables**

**1. **Enter the contingency table into the spreadsheet. The first column should be the row variable. For example, for the data in Table 9, the first column would be employment status. Each subsequent column would be the counts of each category of the column variable. For the data in Table 9, enter the counts for each level of education. Title each column (including the first column indicating the row variable). ** 2. **Select

**Stat**, highlight

**Tables**, select

**Contingency**, then highlight

**with summary**.

**3.**Select the column variables. Then select the label of the row variable. For example, the data in Table 9 has four column variables (Did Not Finish High School, and so on) and the row label is employment status. Decide what values you want displayed. Typically, we choose row percent and column percent for this section. Click Compute!.

**Section 5.1 Probability Rules**

**Simulation**

**1. **Select **Data**, highlight **Simulate Data**, then highlight **Discrete Uniform**. **2. **Enter the number of random numbers you would like generated in the "Rows" cell. For example, if you want to simulate rolling a die 100 times, enter 100. Enter 1 in the "Columns" cell. Enter the smallest and largest integer in the "Minimum" and "Maximum" cell, respectively. For example, to simulate rolling a single die, enter 1 and 6, respectively. Select either the dynamic seed or the fixed seed and enter a value of the seed. Click Compute!. **3. **To get counts, select **Stat**, highlight **Summary Stats**, then select **Columns. 4. **Select the column the simulated data are located in. In the "Group by" cell, select the column the simulated data are located in. In the "Statistics" cell, only select

*n*. Click Compute!.

**Section 6.1 Discrete Random Variables**

**Finding the Mean and Standard Deviation of a Discrete Random Variable**

**1. **Enter the values of the random variable in column var1 and the corresponding frequencies in column var2. Name each column. **2. **Select **Stat**, highlight **Summary Stats**, and select **Grouped/Binned data**. ** 3. **Choose the column that contains the class under the "Bins in:" drop-down menu. Choose the column that contains the frequencies in the "Counts in:" drop-down menu. Select the "Limits" radio button for defining the midpoints. Click Compute!.

**Section 6.2 The Binomial Probability Distribution**

**Computing Binomial Probabilities**

**1. **Select **Stat**, highlight **Calculators**, select **Binomial**. **2. **Enter the number of trials, *n*, and probability of success, *p*. In the pull-down menu, decide if you wish to compute *P*(*X* < *x*), *P*(*X* < *x*), and so on. Finally, enter the value of *x*. Click Compute.

**Section 6.3 The Poisson Probability Distribution**

**Computing Binomial Probabilities**

**1. **Select **Stat**, highlight **Calculators**, select **Poisson**. **2. **Enter the mean, μ. In the pull-down menu, decide if you wish to compute *P*(*X* < *x*), *P*(*X* < *x*), and so on. Finally, enter the value of *x*. Click Compute.

**Section 7.2 Applications of the Normal Distribution**

**Finding Areas Under the Standard Normal Curve**

**1. **Select **Stat**, highlight **Calculators**, select **Normal**. **2. **Enter the mean and the standard deviation. In the pull-down menu, decide if you wish to compute *P*(*X* < *x*) or *P*(*X* > *x*). Finally, enter the value of *x*. Click Compute.

**Finding Scores Corresponding to an Area**

**1. **Select **Stat**, highlight **Calculators**, select **Normal**. **2. **Enter the mean and the standard deviation. In the pull-down menu, decide if you are given the area to the left of the unknown score or the area to the right. If given the area to the left, in the pull-down menu choose the < option; if given the area to the right, choose the > option. Finally, enter the area in the right-most cell. Click Compute.

**Section 7.3 Assessing Normality**

**Normal Probability Plots**

**1. **If necessary, enter the raw data into column var1. Name the column. **2. **Select **Graph, **highlight **QQ Plot**. **3. **Select the variable. Click Compute!.

**Section 9.1 Estimating a Population Proportion**

**1. **If necessary, enter the raw data into column var1. Name the column.

**2. **Select **Stat**, highlight **Proportion Statistics, **highlight **One Sample. **Choose **With Data** if you have raw data, choose **With Summary** if you have summarized data.

**3. **If you chose **With Data**, highlight the column that contains the data in the “Values in:” drop-down menu. Enter the value that represents a success. If you chose **With Summary, **enter the number of successes and the number of observations. ** **Choose the confidence interval radio button. Enter the level of confidence. Leave the method as “Standard-Wald”. Click Compute!.

**Section 9.2 Estimating a Population Mean**

**1. **If necessary, enter the raw data into column var1. Name the column.

**2. **Select **Stat**, highlight **T Statistics, **highlight **One Sample. **Choose **With Data **if you have raw data, choose **With Summary** if you have summarized data.

**3. **If you chose **With Data**, highlight the column that contains the data in the “Select column(s):” drop-down menu. If you chose **With Summary**, enter the sample mean, sample standard deviation, and sample size. Choose the confidence interval radio button. Enter the level of confidence. Click Compute!.

**Section 9.3 Estimating a Population Standard Deviation **

**1. **If necessary, enter the raw data into column var1. Name the column.

**2. **Select **Stat**, highlight **Variance Statistics, **highlight **One Sample. **Choose **With Data **if you have raw data, choose **With Summary** if you have summarized data.

**3. **If you chose **With Data**, highlight the column that contains the data in the “Select column(s):” drop-down menu. If you chose **With Summary**, enter the sample variance and sample size. Choose the confidence interval radio button. Enter the level of confidence. Click Compute!.

**Section 10.2 Hypothesis Tests for a Population Proportion**

**1. **If necessary, enter the raw data into column var1. Name the column.

**2. **Select **Stat**, highlight **Proportion Statistics, **highlight **One Sample. **Choose **With Data** if you have raw data, choose **With Summary** if you have summarized data.

**3. **If you chose **With Data**, highlight the column that contains the data in the “Values in:” drop-down menu. Enter the value that represents a success. If you chose **With S**

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