1. What is the explanatory variable, and what is the response variable?2. What are the populations for the F-test?3. State your hypotheses4. Create side-by-side (or stacked) boxplots for the quantitative variable (IAT Score) grouped by your chosencategorical variable. Select the option to display the mean within the boxplots (directions).Download the StatCrunch output window (your boxplots) and embed the .png file with yourresponse.Do the boxplots suggest that the samples come from populations with different means? Brieflyexplain.SamplePNext, we need to create a table with these summary statistics: sample size, mean, and standard deviation for each of thepopulations you listed above. To do this, use StatCrunch to create a table of the indicated summary statistics for the quantitativevariable (IAT Score) grouped by your chosen categorical variable. The summary statistics should be listed in the order givenwith no other statistics in your table.Copy the table in the StatCrunch output window and paste it into your response.To make your table readily understood by any reader, complete each of the following.A Enter a descriptive title above your table.B.In your table, each group from your chosen categorical variable is labeled with anumber. A reader will not understand what the number represents. Replace thenumeric labels with descriptive words for each group of your selected categoricalvariable (see the Variables section above for your data set).Determine whether conditions are met to use the ANOVA F-test. For each condition explain whythe condition is met or not met.Summary statistics for Sample(IAT-Weight-Score):Group by: Sample(Prefers)Sample(Prefers) n Mean Std. dev. +Strong preference for fatpeople2 Moderate preference for3 Sight preference for fa4Ukes thin people and tpeople equally5 Sight preference for thipeople6 Moderate preference fornin people7 Strong preference for thi5 0.53423182 0.2659270210 0.39895934 0.416370323 0.26406347 0.35412012375 0.368696 0.45337069208 0.50965906 0.37765583145 0.57691726 0.3710883634 0.77391345 0.323849445. Conducting the ANOVA F-test at the 5% significance level:If conditions are met,A. Use StatCrunch to conduct the ANOVA F-test (copy and paste the contents of theStatCrunch output window into your response).B. Identify the F-statistic and the P-value.Then state your conclusion in context.If conditions are not met for your selected categorical variable, start over and use the list ofcategorical variables provided in the Variables section above to select a different categoricalvariable that meets the conditions.If conditions are not met for all categorical variables listed above for your data set, ContactAnalysis of Variance results:Responses: Sample(IAT-Weight-Score)Factors: Sample(Prefers)Response statistics by factorSample(Prefers) ⚫n Mean Std. Dev. Std. Error1 Strong preference for fat 5 0.53423182 0.26592702 0.11892618people2 Moderate preference for ft 10 0.39895934 04163703 0.13166785people3 Sight preference for fat 23 0.26406347 0.35412012 0.07383915people4 Likes thin people and fat 375 0.368696 0.45337069 0.023411962people equaly5 Sight preference for thin 208 0.50965906 0.37765583 0.02618572people6 Moderate preference for thig 45 0.57691726 0.37108836 0.030817211people7 Strong preference forthin peopleANOVA table34 0.77391345 0.32384944 0.05553972SourceDFMSF-Stat P-valueSample(Prefers) 6 9.9180873 1.6530145 9.7612901

Question

1. What is the explanatory variable, and what is the response variable?2. What are the populations for the F-test?3. State your hypotheses4. Create side-by-side (or stacked) boxplots for the quantitative variable (IAT Score) grouped by your chosencategorical variable. Select the option to display the mean within the boxplots (directions).Download the StatCrunch output window (your boxplots) and embed the .png file with yourresponse.Do the boxplots suggest that the samples come from populations with different means? Brieflyexplain.SamplePNext, we need to create a table with these summary statistics: sample size, mean, and standard deviation for each of thepopulations you listed above. To do this, use StatCrunch to create a table of the indicated summary statistics for the quantitativevariable (IAT Score) grouped by your chosen categorical variable. The summary statistics should be listed in the order givenwith no other statistics in your table.Copy the table in the StatCrunch output window and paste it into your response.To make your table readily understood by any reader, complete each of the following.A Enter a descriptive title above your table.B.In your table, each group from your chosen categorical variable is labeled with anumber. A reader will not understand what the number represents. Replace thenumeric labels with descriptive words for each group of your selected categoricalvariable (see the Variables section above for your data set).Determine whether conditions are met to use the ANOVA F-test. For each condition explain whythe condition is met or not met.Summary statistics for Sample(IAT-Weight-Score):Group by: Sample(Prefers)Sample(Prefers) n Mean Std. dev. +Strong preference for fatpeople2 Moderate preference for3 Sight preference for fa4Ukes thin people and tpeople equally5 Sight preference for thipeople6 Moderate preference fornin people7 Strong preference for thi5 0.53423182 0.2659270210 0.39895934 0.416370323 0.26406347 0.35412012375 0.368696 0.45337069208 0.50965906 0.37765583145 0.57691726 0.3710883634 0.77391345 0.323849445. Conducting the ANOVA F-test at the 5% significance level:If conditions are met,A. Use StatCrunch to conduct the ANOVA F-test (copy and paste the contents of theStatCrunch output window into your response).B. Identify the F-statistic and the P-value.Then state your conclusion in context.If conditions are not met for your selected categorical variable, start over and use the list ofcategorical variables provided in the Variables section above to select a different categoricalvariable that meets the conditions.If conditions are not met for all categorical variables listed above for your data set, ContactAnalysis of Variance results:Responses: Sample(IAT-Weight-Score)Factors: Sample(Prefers)Response statistics by factorSample(Prefers) ⚫n Mean Std. Dev. Std. Error1 Strong preference for fat 5 0.53423182 0.26592702 0.11892618people2 Moderate preference for ft 10 0.39895934 04163703 0.13166785people3 Sight preference for fat 23 0.26406347 0.35412012 0.07383915people4 Likes thin people and fat 375 0.368696 0.45337069 0.023411962people equaly5 Sight preference for thin 208 0.50965906 0.37765583 0.02618572people6 Moderate preference for thig 45 0.57691726 0.37108836 0.030817211people7 Strong preference forthin peopleANOVA table34 0.77391345 0.32384944 0.05553972SourceDFMSF-Stat P-valueSample(Prefers) 6 9.9180873 1.6530145 9.7612901 <0.0001Error793 134.28968 0.16934386Total799 144.20777

Accepted Answer

1. **Explanatory and Response Variables**:
   - The explanatory variable (independent variable) is…