# Statdisk User Manual 13.0.0

STAT 3001

Table of Contents

Open a File …………………………..………………………………………………………………4

Edit Column Titles …………………………………………………………………………………..4

Copy a Dataset ………………………………………………………………………………………5

Paste a Dataset ………………………………………………………………………………………5

Sort a Dataset ………………………………………………………………………………………..6

Sample Transformations …………………………………………………………………………….6

Descriptive Statistics ………………………………………………………………………………..7

Creating a Histogram ……………………………………………………………………………….8

Creating Boxplots …………………………………………………………………………….….…9

Normal Distribution …………………………………………………….………………….…….…9

Confidence Intervals ……………………………………………………………………….………11

Hypothesis Testing ………………………………………………………………………….….…..12

Correlation and Regression ………………………………………………………………….….….13

Multiple Regression …………………………………………………………………….…….……14

Chi-Square Goodness-of-Fit …………………………………………………………………….…15

Chi-Square Test of Independence …………………………………………………………………18

One-Way Analysis of Variance ……………………………………………………………………19

When you open the Statdisk program you will see the screen shown in Figure 1. Be certain that you are using Version 13.0.0. Click on the OK button to close the Statdisk information screen.

Figure 1

You can perform all Statdisk functions from the Sample Editor Screen. The top of the screen has the following menus: **File, Edit, Analysis, Data, Datasets, Window**, and **Help** as shown in Figure 2.

Figure 2

Along with performing statistical calculations, Statdisk is also compatible with many popular software application packages. You can import, copy, paste, save, print and transform data sets. You can also copy, paste, save, or print any of the Statdisk numerical or graphical outputs and export them into other programs such as Microsoft Word. Those options are available as clickable buttons at the top of the **Sample Editor** screen as shown in Figure 3.

Figure 3

Opening a File

Statdisk has numerous datasets stored in the program and can be accessed by clicking on **Datasets **at the top of the **Sample Editor** window. After opening **Datasets **go to **Elementary Statistics 13th Edition.** The names of the datasets will appear to the right. Click on **Body Data **and the data values will appear in the **Sample Editor** as shown in figure 4.

Figure 4

You can preview the datasets quickly by opening a data set, review the data, and then select **Clear** to move in to the next file. You can also access datasets that Statdisk has available online by going to **Help** and then **Triola Statistics Series.**

Using Data Tools

After you have opened a dataset or have typed in data to the **Sample Editor**, you can edit column titles, sort data, delete columns, add columns or rows, or explore the data set by opening the **Data Tools** menu. The **Data Tools** button is located at the top of the **Sample Editor** page.

To Edit column titles open up **Data Tools** and then **Edit column titles. **Type in the names of the column titles into the box shown in Figure 5.

Figure 5

Click on the **Save Changes** button to enter the new column titles.

Copy and Paste

The Copy button is at the top of the **Sample Editor** Screen.

To copy columns from a data set simply click on the **Copy** button and a screen will appear asking you which column of data you want to copy (see figure 6). You can copy all of the columns or select columns. To **Paste** the column of data values into another column. Click on the column title (or number) then open the **Edit** menu and select **Paste**.

Figure 6

Sort Data

To sort data, select Data Tools and then select **Sort Data. **Use the drop-down arrow to select** Sort One column, **then select the column title and order from A to Z (see figure 7). Then click on **Sort**. The data values in that column will be sorted from lowest value to highest value.

Figure 7

**The Data Menu**

The two main menus in Statdisk are **Analysis** and **Data.**

The **Data** menu is used to sort data, add data, transform data, generate descriptive statistics including charts and graphs, assess normality and generate sets of data values that emulate one of the standard types of statistical distributions.

The **Analysis** menu is use to find area under the curve for many of the standard statistical distributions, determine sample size, create confidence intervals, perform hypothesis tests for parametric and non-parametric models.

Using the Data Menu

To transform a dataset you first need to type data into the sample editor or select an existing dataset. Open the **Body Data** file that was referenced in Opening a File earlier in the manual. Select **Data** and then **Sample Transformations **to open the **Sample** **Transformer** widow (see Figure 8). The Source column is the column containing the dataset that you want to transform. Select the operation that will be used to change the data values and type in the constant that you will add, subtract, multiply, divide, mod value, or raise to a power to the data values. After you click on **Basic Transform** the new data set will appear in the **Sample Transformer** window.

Figure 8

Descriptive Statistics

The descriptive statistics of a data set can be found by opening the **Data** menu and selecting **Descriptive Statistics.** Select the column that the data set is in and then click on **Evaluate.** A list of the most commonly used numerical descriptive statistics will be shown (see figure 9).

Figure 9

Histogram

A visual display of a single set of data values can be shown by opening the **Data** menu and then selecting **Histogram**.

Select the column that the data values are in. If you would like the Statdisk program to automatically select the class width and the class start, select Auto-fit. You can display the count or the frequency for each class by selecting **Bar Labels**. Click on **Plot** to display the graph (see figure 10).

Figure 10

You can also Print, Copy or Save the histogram and later paste the display in a Word file.

Boxplots

If you would like to compare two or more sets of data values you can plot them on one graph by using boxplots. Open the Data menu and select **Boxplot**. Then select the columns containing the data values that you would like to compare. You can then select **Boxplot** to show a standard view of the boxplots or **Modified Boxplot** which will emphasize outliers (see figure 11).

Figure 11

**Using the Analysis Menu**

Statdisk can perform many basic statistical functions relating to probability distributions, confidence intervals, hypothesis testing, correlation and regression, Chi-square and other non-parametric tests, and sample-size determination. This manual will explain how to perform many of those basic statistical functions.

Normal Distribution

You do not need to have a set of data values in the Sample Editor to use the probability distribution functions. Open the **Analysis** menu and select **Probability Distributions**. The first four functions, Normal Distribution, Student-t Distribution, Chi-Square Distribution, and the F Distribution perform the same type of tasks. Select Normal Distribution. The screen shown in Figure 12 will appear.

Figure 12

You can enter a Z value into the box to the right of **z Value:** or you can enter an amount of area to the left of some Z value under the standard normal distribution in the box to the right of **Cumulative area from the left:. **Figure 13 shows the standard normal distribution with Z-values along the bottom axis and the area under the curve between the given Z-values. Statdisk will find the given values and any other values that are not shown on the table.

Figure 13

Open the **Analysis** menu and then select **Probability Distributions** and then **Normal Distribution**. Enter -1 into the box for **Z Value** and then click on **Evaluate**. Figure 14 shows the Statdisk output.

Figure 14

The output gives the discrete probability of getting -1 or .2419707. It also gives the cumulative area to the left of -1 or .158655. If you add the areas to the left of -1 shown in Figure 13 you will get the same amount.

If you put in any value between 0 and 1 representing the area to the left of a Z score and then press **Evaluate **you will get the associated Z value.

Confidence Intervals

To find a confidence interval for a sample statistic you do not need to type in any data values or have a dataset in the **Sample Editor. **For example, to find a confidence interval for one-sample mean open up the **Analysis** menu then select **Confidence Intervals **and then **Mean-One Sample**. Figure 15 shows the Statdisk output screen for a 95% confidence interval with a sample mean of 26.7, a sample standard deviation of 4.1, and a sample size of 40. The confidence interval of 25.29 to 28.01 is given. The Margin of error is the distance from the mean to the upper value and the distance from the mean to the lower value of the confidence interval.

Figure 15

If you are given a set of data values and not given any of the sample statistics such as the mean and standard deviation you must first use **Descriptive Statistics** to find the values needed to enter into the **Confidence Interval: Mean-One Sample **window that is shown in Figure 15.

Hypothesis Testing

The hypothesis testing procedures in Statdisk are very similar to the confidence interval procedures. To perform a hypothesis test about a one-sample mean open up the **Analysis** menu and then select **Hypothesis Testing**, and then **Mean-One Sample**. Figure 16 shows the Statdisk output for an alternative hypothesis that the population mean is equal to the claimed mean. The claimed mean is equal to 25 and the sample mean is 23.7 with a sample standard deviation of 4.5 with a sample size of 32. The hypothesis is tested at the .05 level of significance. After you select **Evaluate**, you get the information shown in Figure 16. The information is provided on the right of the screen for the provided inputs.

Figure 16

As with confidence intervals if you are given a set of data values and not given any of the sample statistics such as the mean and standard deviation you must first use **Descriptive Statistics** to find the values needed to enter into the **Hypothesis Testing: One Mean **window that is shown in Figure 16. Figure 17 shows a normal probability plot representing the visual interpretation of the hypothesis test.

Figure 17

Correlation and Regression

To compute a correlation or create a regression equation you first need to type data into the **Sample Editor** or select an existing dataset. Open **Datasets**and select **Elementary Stats 13th Edition**. Open the **IQ and Brain Size** dataset. Select **Analysis** and then **Correlation and Regression.** Select column 4 for the x-variable and column 5 for the y-variable and then click on **Evaluate** (see Figure 18). The information for both the correlation and the regression is shown in the output window on the right.

Figure 18

If you click on **Plot** a scatterplot of the correlation data and the line-of-best fit from the regression will be displayed (see Figure 19).

Figure 19

Multiple Regression

To generate a multiple regression equation you first need to type data into the **Sample Editor** or select an existing dataset. Open **Datasets** and select **Elementary Stats 13th Edition**. Open the **IQ and Brain Size** dataset. Select **Analysis** and then **Multiple Regression.** Select columns 4, 5, and 8 to be included in the regression analysis. Select 4 for the Dependent variable column. Click on **Evaluate **to generate the multiple regression statistics (see Figure 20). Your regression equation with rounded coefficients would be y = 29.4 – .019X1 + 1.65X2 The efficiency of the regression equation would be the Adjusted R2 value.

Figure 20

Chi-Square Goodness-of-Fit : Equal Expected Frequencies

To generate a Goodness-of-Fit test you must first type data into the **Sample** **Editor** or select an existing dataset. Imagine that a company wants to know if auto accidents occur equally throughout the days of the week. Use the **Clear** button at the top-left of the **Sample Editor** screen to erase any existing data. The number of accidents that occur each day of the week are as follows:

M | T | W | TR | F |

45 | 36 | 17 | 29 | 52 |

Type the data into column 1, then use the **Edit** **Column Titles** option under the **Data Tools** button at the bottom of the **Sample Editor** screen to name List 1: Accidents (see Figure 21).

Figure 21

Select **Analysis** and then **Goodness-of-fit. **Chose **Equal Expected Frequencies** since the company is testing to see if accidents occur equally. Set the significance level to 0.05 and select 1 as the column to be the Observed Frequencies. Click on **Evaluate** to generate the Goodness-of-Fit test. The results are shown in the output window to the right (see Figure 22).

Figure 22

Press **Plot** to view a visual representation of the Chi-Square Distribution of the data. The graph shows the Critical Value, X2 : 9.488 and the Test Statistic, X2: 20.860 (see figure 22).

Goodness-of-Fit: Unequal Expected Frequencies

An ice cream company wishes to discover the popularity of their offered ice cream flavors. The Expected frequencies are given:

Vanilla | Chocolate | Strawberry | Other |

42% | 33% | 14% | 11% |

The University of Florida surveyed a sample size of n=250 students questioning their *preferred* ice cream flavor. The observed data collected is shown in the table below.

Vanilla | Chocolate | Strawberry | Other |

114 | 68 | 47 | 21 |

In order to generate the goodness-of-fit test, the data must be entered into the Sample Editor. Use the **Clear** button at the bottem of the **Sample Editor**screen to erase any existing data. Enter the observed values into List 1 and enter the expected frequencies into List 2. Click on **Analysis** and then **Goodness-of-Fit**. Chose the **Unequal Expected Frequencies** option since the company is not testing to see if the flavors are equally popular. Because the expected frequencies were given as proportions, chose the **As** **Proportions** option under **Enter Expected Frequencies (as decimals)**. Set the **Observed Column** option as 1 and the Expected Column option as 2. We will set the Significance level to 0.05. Click **Evaluate** (see Figure 25).

Figure 25

Click **Plot** to view a visual representation of the Chi-Square Distribution. The Critical Value, X2 is shown as 7.815 and the Test Statistic, X2 is shown as 8.971 (see Figure 26).

Figure 26

Chi-Square Test of Independence (Contingency Tables)

To generate a Contingency table test you must first type data into the Sample editor or select an existing data set. A company seeks to discover which color of car that males prefer and which color of car that females prefer. Use the **Clear** button at the bottem of the **Sample Editor** screen to erase any existing data. The data collected is as follows:

Red | Blue | Green | White | |

Male | 21 | 17 | 44 | 8 |

Female | 28 | 24 | 14 | 18 |

Enter the data into the Sample Editor exactly as it is shown in the table (see Figure 27).

Figure 27

Select** Analysis** and then **Contingency Tables**. Then chose columns 1, 2, 3 and 4 to include in the analysis. We will set the significance level ot 0.05. Click **Evaluate** to view the results shown in the output window to the right (see Figure 28).

Figure 28

Click **Plot **to display a visual of the Chi-Square Distribution. The Critical Value, X2 is shown to be 7.815 and the Test Statistic, X2 is shown to be 21.377 (see Figure 29).

Figure 29

One-Way Analysis of Variance (ANOVA)

To use the Analysis of Variance (ANOVA) function in Statdisk you first need to type data into the sample editor or select an existing dataset. Go to Elementary Statistics 13th Edition and select the **Garbage Weights** dataset. Go to the **Analysis** menu and then select **One-Way Analysis of Variance.**Select columns 2, 3, and 4 and click on **Evaluate**.

Figure 30.

The hypothesis testing results are shown in the box on the right. (see figure 30.)

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