Question
Correlation
This assignment will examine your ability to analyze the relationship between two variables, create an equation for predicting one variable from the other, and to critique the results of the data. You will be given the data for 2 psychological experiments looking at the relationship between variables. For these sets of data you will: (1) use the SPSS program to calculate the correlation and create a scatterplot (2) provide the appropriate output given from the program (3) describe this relationship (both strength and direction, and in laymans terms) (4) determine if these variables truly related or could there be a third variable at play (5) calculate the regression equation (showing your work) (6) use that regression equation to calculate a prediction; and (7) calculate the proportionate reduction in error. All work will be posted in a word document and uploaded to blackboard 1) A psychologist is investigating the relationship between drinking coffee and sleep. She chooses 20 participants and measures how many cups of coffee they had the previous day and how many hours of sleep they got the night before. The data is presented below Coffee Sleep 09.5 9.5 6 8.5 6
6 67.5S 2 0 6 6 For this data you will: Use the SPSS program to calculate the correlation and create a scatterplot Provide the appropriate output How would you describe this relationship? (both strength and direction, and in laymans terms) Are these variables truly related or could there be a third variable at play? Calculate the regression equation (show your work) How much sleep should someone get if they drink 5 cups of coffee in a day? Calculate the proportionate reduction in error . . 2] A psychologist is investigating the relationship of ambient temperature and water consumption. She chooses 20 participants and measures how much water they consumed throughout the course of a day and what the high temperature was for that day. The data is presented below Temperature Water consumption 75 16 20 25 27 32 48 48 85 92 97 87
No Spacing Heading 1 Heading 2 78 98 89 98 78 92 84 71 14 41 45 19 41 38 23 29 27 78 For this data you will: Use the SPSS program to calculate the correlation and create a scatterplot Provide the appropriate output How would you describe this relationship? (both strength and direction, and in laymans terms) Are these variables truly related or could there be a third variable at play? Calculate the regression equation (show your work) How much water should someone drink if the high temperature for that day was 70 degrees? Calculate the proportionate reduction in error . □ Focus
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Answer #1

Steps to find the correlation in SPSS

Analyze -> correlate -> Bivariate -> check pearson's -> Ok

We get the following output

CORRELATIONS /VARIABLES coffee sleep /PRINT TWOTAIL NOSIG MISSING PAIRWISE Correlations [Dataset0] Correlations coffee sleep 1.621 003 20 coffee Pearson Correlation Sig. (2-tailed) 20 .621 sleep Pearson Correlation Sig. (2-tailed) 003 20 20 **. Correlation is significant at the 0.01 level (2- tailed)

Coffee and sleep are negatively correlated with -0.621 coefficient of correlation.

Which implies that more the coffee less the sleep.

We have the following steps for creating a scatter plot:

Graph -> Legacy Dialogue -> Scatter plot -> Simple scatter plot ->X axis(Coffee) Y axis(Sleep) -> ok

We get the following graph

GRAPH SCATTERPLOT (BIVAR)coffee WITH sleep /MISSING LISTWISE Graph [DataSet0] 10.0 9.0 8.0 5.0 coffee

These variables might not be truly correlated a third variable might be at play which may have been the person's ability to be awake.

The regression equation is given as :

The independent variable is Coffee, and the dependent variable is sleep. In order to compute the regression coefficients, the following table needs to be used Coffee slee Coffee sleep 9.5 9.5 7.0 6.0 8.0 8.5 8.0 6.0 6.0 7.0 7.0 7.5 8.5 9.0 9.0 7.0 5.0 6.0 7.0 6.0 147.5 90.25 9.5 90.25 16 30 25 25.5 72.25 16 49 45 56.25 72.25 81 81 17 16 25 18 35 25 Sum 60 410 1121.25

Based on the above table, the following is calculated 60 20 1-1 147.5 20 72 is] ssrl y. Y,2--I yr:) 1 121.25-147.52/20-33.4375 Y:) = 410-60 x 147.5/20 =-32.5 Therefore, based on the above calculations, the regression coefficients (the slope m, and they intercept n) are obtained as follows -32.5 82 =-0.3963 = SSxx n-I -Xm 7.375 3 x (-0.3963) 8.564 Therefore, we find that the regression equation is: sleep 8.564-0.3963Coffee

Sleep=8.564-0.3963*5=6.58 hours of sleep.

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