In-Class SPSS Problem Set_SPSS Exercise_1 (1)

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Week 8 In-Class Activity: SPSS Exercise #1 Go to AppsAnywhere, Sheridan College @ https://apps.sheridancollege.ca/ When you are in AppsAnywhere, the system might ask you to install the application, if you don’t have it already – so, please go ahead and install the application. Once you are in AppsAnywhere, scroll down to find Sheridan Virtual Desktop > then click Launch > Launch the Client > Pick your Sheridan Account > Click General Purpose => You should now be in Sheridan Virtual Desktop (depending on the way your laptop is setup, these steps might be slightly different). Click AppsAnywhere icon again on your Virtual Desktop > Find and Launch SPSS 28 Bring the data analysis Excel File in your Virtual Desktop (copy from Slate and paste in Virtual Desktop) Import the Data in SPSS from Excel. Follow this path: File > Import Data > Excel > Choose Data Analysis Excel File > Open > Check Appropriate Boxes > OK Set the hypothesis to test the association between gender and cola preference. Cross-tabulate the respondents’ genders with cola preference and test the hypothesis. Do you see any statistically significant association between gender and cola preference? Explain. Hypotheses: H0: There is no association between sex and cola preference. H1: There is an association between sex and cola preference. SPSS procedure: Analyze > Descriptive Statistics > Crosstabs > Drag and drop one variable in Row box and the other in Column box > Statistics > Check off Chi-square > Continue > OK Note: Chi-square test in cross tabulation is used to test the association between categorical variables only (We will use a level of significance of 5%). Go to Output window to see the results. Report cross-tabulation and Chi-square results.
There is no association between sex and cola preference. It is because since p-value (1.000) is greater than the level of significance (5% or 0.05), we fail to reject H0 (as per p-value method). In-Class Work_SPSS Exercise #2 1. Formulate a statistical hypothesis appropriate for the consumer group’s purpose. H0: The mileage of the car is 30 miles per gallon or µ = 30 (or, there is no difference between sample mean and population mean). H1: The mileage of the car isn’t 30 miles per gallon or µ ≠ 30 (or, there is a difference between sample mean and population mean). 2. Calculate the mean (average) miles per gallon and the sample standard deviation. SPSS procedure: Analyze>Compare Means>One-Sample T Test>Drag and drop variable in Test Variable(s) box>Enter Test Value as 30>OK
Mean = 28.17 Standard Deviation = 3.03 3. Conduct an appropriate hypotheses test to decide whether or not Premier Motorcar’s claim is correct, using a 0.05 significance level. Since critical value (rule of thumb value is 2, or from the table – 2.064, two tailed test) is less than test statistics (3.013, ignore negative sign), we reject H0. Therefore, the Premier Motorcar’s claim is false. In-Class Work_SPSS Exercise #3 1. Paired Samples t-test Used to test the difference in means between two groups with paired observations. H0: There is no difference in distance run between the groups of protein and carb-protein. (or, μ 1 = μ 2 ) H1: There is a difference in distance run between the groups of protein and carb-protein. (or, μ 1 ≠μ 2 ) (two-tailed test) SPSS procedure: Analyze>Compare Means>Paired Samples T Test>Drag two variables under Variable 1 and Variable 2 on the right (doesn’t matter where you place them)> OK Go to Output window to see the results. Choose the third table.
Findings: Since p-value (0.000) is less than the level of significance (0.05), we reject H0 (used p- value method). Decision: There is a difference in distance run between the groups of protein and carb-protein. 2. Independent samples t-test Used to test the difference in means between two groups with independent observations. H0: There is no difference in engagement with TV between male and female. (or, μ 1 = μ 2 ) H1: There is a difference in engagement with TV between male and female. (or, μ 1 ≠μ 2 ) (two- tailed test) SPSS procedure: Analyze>Compare Means>Independent-Samples T Test>Drag Engagement variable to the right in the top box and gender in the grouping variable box>Click Define Groups> Enter 1 under Group 1 and 2 under Group 2 (note the numbers 1 and 2 comes from the way your gender variable has been coded. If they were defined as F and M, for example, you should enter F and M here)>Continue>OK Go to Output window to see the results. Choose the table in the middle. Findings: There are two rows and you need to pick the first row because equal variance is assumed as p-value. Since p-value (0.023) is less than the level of significance (0.05), we reject H0 (as per p-value method). Decision: There is a difference in engagement with TV between male and female. 3. One-Way ANOVA
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