PSY3901: Experimental Psychology 1 Week 6 Assignment Written Responses Week 6 Assignment: Correlation and Regression Written Response Worksheet NAME: Instructions: Follow along with the step-by-step...

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PSY3901: Experimental Psychology 1 Week 6 Assignment Written Responses Week 6 Assignment: Correlation and Regression Written Response Worksheet NAME: Instructions: Follow along with the step-by-step instruction manual provided for the Week 6 assignment. The instruction manual will make specific reference to data interpretation questions that require written responses. Use this worksheet to answer these written response questions. Each question is listed below along with the number of points each question is worth toward the assignment. Type your response in the space provided below each question. QUESTION 1 3 points Based on the correlation coefficient between happiness score at Time 1 and Time 2, does the happiness measure appear to have sufficient test-retest reliability? In your response, report the Pearson r, and explain the criteria you used to make your determination. QUESTION 2 3 points Based on the Cronhbach’s alpha statistic, does the four-item happiness measure appear to have sufficient internal consistency (interitem reliability)? In your response, report Cronhbach’s alpha, and explain the criteria you used to make your determination. QUESTION 3 3 points As you examine the interitem correlation matrix and the item-total atatistics (Cronbach’s alpha if in the item deleted column) included in the reliability analysis output, it indicates that one of the four items on the happiness measure is not as strongly correlated as the other three items. Report which item (1, 2, 3 or 4) the output indicates as being a relatively weaker fit (i.e., not as strongly related with the others) in the measure and what the Cronbach’s alpha would be if this item were to be excluded from the scale. QUESTION 4 3 points Based on your intuition, do you expect that there will be a positive relationship, negative relationship, or no relationship between body mass index and self-esteem? Describe the predicted relationship and provide a brief one-sentence rationale for your prediction. QUESTION 5 5 points Paste the scatterplot figure you created showing the relationship between body mass index and self-esteem. Include an APA style title with the figure. PASTE SCATTERPLOT FIGURE BELOW: QUESTION 6 3 points Describe the nature of the relationship between body mass index and self-esteem score based on the scatterplot figure. What is the direction and strength of the relationship? QUESTION 7 5 points In about two sentences, report and interpret the results of the Pearson correlation in APA style. Report the correlation coefficient in correct statistical notation. Also report the coefficient of determination as a measure of effect size. Finally, interpret the findings (i.e., was there evidence for a significant relationship between body mass index and self-esteem? If so, what was the nature of the relationship?) INCLUDE RESPONSE IN APA FORMAT BELOW: Results QUESTION 8 3 points Interpret and report the correlations between each of the predictor variables (self-esteem, physical health, and psychological health) and the outcome variable happiness. Describe which variables are related to happiness, how they are related, and the strength of the relationships. QUESTION 9 5 points Write a brief report in APA style summarizing the results of the regression analysis specified in Model 1 that examined if self-esteem was a significant predictor of happiness. Report and interpret the R-square of the model. Also, report the ANOVA table results and the standardized coefficient weight (Beta) for the self-esteem score for Model 1. Finally, provide at least one sentence interpreting the findings (i.e., is self-reported self-esteem a good predictor of self-reported happiness?) INCLUDE RESPONSE IN APA FORMAT BELOW: Results QUESTION 10 2 points Specify the regression equation [HappyScorei = b0 + bSelfEsteemScore × SelfEsteemScorei] for Model 1 that examined self-esteem as a predictor of happiness. *Hint: Enter the B-values into the equation above for b0 (B-value for the Model 1 Constant) and bSelfEsteemScore (B-value for SelfEsteeemScore in Model 1). QUESTION 11 2 points Using the regression equation for the regression Model 1 you just specified in Question #9 above, what would the predicted happiness score (Predicted-Y) be for someone who has a self-esteem score (X) of 30? *Hint: Enter 30 in the regression equation for SelfEsteemScorei and solve for HappyScorei QUESTION 12 3 points Examining the model summary table for Model 2 in the multiple regression output, did the addition of physical health score and psychological health score as predictors improve the fit of the model (i.e., improve the amount of explained variability in happiness scores)? In your answer, report and interpret the R-square change for Model 2 and report the F change results. QUESTION 13 3 points Examining the coefficients table for Model 2 in the multiple regression output, which variables were found to be significant predictors of self-reported happiness? In your answer, report and interpret the standardized coefficient weights (Beta) and the t-statistics associated with each predictor in the Model 2 regression analysis. QUESTION 14 2 points Overall, based on the measures in the multiple regression analysis, does self-esteem, physical health, or psychological health appear to be the most influential predictor of happiness? Provide evidence from the output supporting your answer. 1 PSY3901: Experimental Psychology 1 Week 6 Assignment: Correlation and Regression in SPSS 1 Week 6 Assignment: Correlation and Regression in SPSS Step-by-Step Instruction Manual Week 6 Assignment Overview For this week’s assignment, you will use a modified version of the health and self-esteem dataset that we have used on previous assignments. You will be given research tasks that require the use of correlational and regression techniques in SPSS to examine relationships between variables included in the dataset. Along the way you will be asked to interpret and report the results by following the questions on your Week 6 assignment written response worksheet. The Week 6 SPSS assignment is worth a total of 60 points. To complete the assignment, you will need to upload and submit the following two files for grading: o SPSS Output (.spv) file; this file includes a log of all commands and outputs requested during your SPSS session for this assignment o Week 6 Assignment Written Response Worksheet (MS Word file); this file includes your written responses to data interpretation questions Assignment Materials Download, update, save, and submit the files listed below for this assignment: o PSY3901 Week 6 Assignment Dataset (Health and Self-Esteem) (SPSS .sav file) o PSY3901 Week 6 Assignment Written Response Worksheet (MS Word File) Step-by-Step Instructions 1: Open the Dataset and Create a New Output File for the Assignment 1. Open the Week 6 assignment dataset. 2. Open a new SPSS output file to keep track of all your SPSS activity during the assignment. 3. Add a header to your output file that reads: PSY3901 Week 6 SPSS Assignment – YOUR NAME. 4. Save the output file. Be sure to log all assignment SPSS activity in this output file, and save it regularly. You will be submitting this output file as part of your assignment. 2: Examining the Test-Retest Reliability of Happiness Score Measure (2 points for output) As you survey the health and self-esteem dataset for Week 6, you will notice one new variable included within the dataset with the name HappyScore2. In order to obtain the HappyScore2 measure, we had the same participants come back five weeks later to fill out the same four-item happiness measure. We then computed their overall happiness score on this measure again. The purpose of having the same participants fill out the same measure a second time was to evaluate the test-retest reliability of the happiness measure. If a measure is consistent over time (i.e., has test-retest reliability), then participants should obtain very similar scores on the measure each time it is administered. We can use PSY3901: Experimental Psychology 1 Week 6 Assignment: Correlation and Regression in SPSS 2 a Bivariate Correlation in SPSS to test if the happiness measure has strong test-retest reliability. In SPSS, run a correlation between HappyScore and HappyScore2 to examine if the measure has sufficient test-retest reliability. In this case, we are not interested in if the correlation is significant, but rather the overall strength of the correlation coefficient. Specifically, the correlation should be +.70 or above for us to feel confident about the test-retest reliability of the happiness measure used in our survey. 1. Go to Analyze  Correlate  Bivariate… 2. Add the HappyScore and HappyScore2 from the variable list to the Variables: box. Under Correlation Coefficients make sure that Pearson is checked, and under Test of Significance make sure Two-tailed is selected. Under Options… you can choose Means and standard deviations and Cross-product deviations and covariances if you like. 3. Click OK to run the correlation. 4. Use the Pearson correlation output to answer Question #1 on your Assignment 6 written response worksheet. QUESTION 1 3 points Based on the correlation coefficient between happiness score at time 1 and time 2, does the happiness measure appear to have sufficient test-retest reliability? In your response, report the Pearson r, and explain the criteria you used to make your determination. 3: Internal Consistency (Inter-Item Reliability) of the Happiness Measure (3 points for output) Another type of the reliability that is of interest for the happiness measure is internal consistency or inter-item reliability. In this case, what we are interested in is if all four items included on the happiness measure are consistent with one another (i.e., are all measuring the same variable or construct). To examine if the four-item happiness measure has sufficient internal consistency, use Reliability analysis in SPSS to generate Cronbach’s alpha, inter-item correlations, and “Scale if item deleted” descriptives. An overall Cronhbach’s α of .70 or above usually provides sufficient evidence for high internal consistency across items on a measure. 1. Go to Analyze  Scale  Reliability Analysis… 2. Add the four happiness measure items (Happy1, Happy2, Happy3, and Happy 4_Reverse) from the variable list to the Items: box. Under Model, make sure that Alpha is selected from the drop- down menu options. 3. Click the Statistics… button and, under Descriptives for, check to include Scale if item deleted. Also, under Inter-Item, check the Correlations box. Then click Continue. 4. Click OK to run the correlation. 5. Use the Reliability Analysis output to answer the questions shown below on your Assignment 6 written response worksheet. PSY3901: Experimental Psychology 1 Week 6 Assignment: Correlation and Regression in SPSS 3 QUESTION 2 3 points Based on the Cronhbach’s Alpha statistic, does
Answered Same DayJun 11, 2021

Answer To: PSY3901: Experimental Psychology 1 Week 6 Assignment Written Responses Week 6 Assignment:...

Medhini answered on Jun 13 2021
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PSY3901: Experimental Psychology 1
Week 6Assignment Written Responses
;Week 6Assignment: Correlation and Regression
Written Response Worksheet
    NAME:
    
Instructions: Follow along with the step-by-step instruction manual provided for the Week 6assignment. The instruction manual will make specific reference to data interpretation questions that require written responses. Use thi
s worksheet to answer these written response questions. Each question is listed below along with the number of points each question is worth toward the assignment.Type your response in the space provided below each question.
    QUESTION 1
    3 points
    Based on the correlation coefficient between happiness score at Time 1 and Time 2, does the happiness measure appear to have sufficient test-retest reliability? In your response, report the Pearson r, and explain the criteria you used to make your determination.
    Pearson correlation value r is 0.744 there is a very strong positive correlation between happiness score at Time1 and Time2 . To make this decision I used pearson correlation value ,In this output we can seen

    Descriptive Statistics
    
    Mean
    Std. Deviation
    N
    Overall Happiness Score (Sum of 4 Items)
    19.00
    5.110
    93
    Overall Happiness Score (Sum of 4 Items) on Measure 5 Weeks Later
    19.81
    5.361
    69


    
    
    Overall Happiness Score (Sum of 4 Items)
    Overall Happiness Score (Sum of 4 Items) on Measure 5 Weeks Later
    Overall Happiness Score (Sum of 4 Items)
    Pearson Correlation
    1
    .744**
    
    Sig. (2-tailed)
    
    .000
    
    Sum of Squares and Cross-products
    2402.000
    1294.354
    
    Covariance
    26.109
    20.224
    
    N
    93
    65
    Overall Happiness Score (Sum of 4 Items) on Measure 5 Weeks Later
    Pearson Correlation
    .744**
    1
    
    Sig. (2-tailed)
    .000
    
    
    Sum of Squares and Cross-products
    1294.354
    1954.551
    
    Covariance
    20.224
    28.743
    
    N
    65
    69
    **. Correlation is significant at the 0.01 level (2-tailed).
These two table tells about the correlation and mean and standard deviation for the variable

    QUESTION 2
    3 points
    Based on the Cronhbach’salpha statistic, does the four-item happiness measure appear to have sufficient internal consistency (interitem reliability)? In your response, report Cronhbach’salpha, and explain the criteria you used to make your determination.
    From our example, we can see that Cronbach's alpha is 0.838, which indicates a high level of internal consistency for our scale with this specific sample.
Yes the four-item happiness measure appear to have sufficient internal consistency . using the cronhbach’s alpha I concluded the result
    Correlations
    
    Overall Happiness Score (Sum of 4 Items)
    Overall Happiness Score (Sum of 4 Items) on Measure 5 Weeks Later
    Overall Happiness Score (Sum of 4 Items)
    Pearson Correlation
    1
    .744**
    
    Sig. (2-tailed)
    
    .000
    
    Sum of Squares and Cross-products
    2402.000
    1294.354
    
    Covariance
    26.109
    20.224
    
    N
    93
    65
    Overall Happiness Score (Sum of 4 Items) on Measure 5 Weeks Later
    Pearson Correlation
    .744**
    1
    
    Sig. (2-tailed)
    .000
    
    
    Sum of Squares and Cross-products
    1294.354
    1954.551
    
    Covariance
    20.224
    28.743
    
    N
    65
    69
    **. Correlation is significant at the 0.01 level (2-tailed).
    QUESTION 3
    3 points
    As you examine the interitem correlation matrix and the item-total statistics (Cronbach’s alpha if in the item deleted column) included in the reliability analysis output, it indicates that one of the four items on the happiness measure is not as strongly correlated as the other three items. Report which item (1, 2, 3 or 4) the output indicates as being a relatively weaker fit (i.e., not as strongly related with the others) in the measure and what the Cronbach’s alpha would...
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