Statistical Knowledge Homework
jokoz13
Concept10.docxWeek #10: Concept Activity (10 points)
Objective: The purpose of this concept activity is for you to practice interpreting statistical output and explaining what the output means for Pearson correlation and regression analyses.
Directions: Below you will find output for the two inferential tests we covered this week (Pearson correlation and regression). For each test, read the explanation that is provided. These explanations will give you background information on the purpose of the study. After reading the explanation you will interpret the output. Look through the output and use it to answer the questions below. Hint: it is best to go through the lectures first. Then, if necessary, go back with the concept activity sheet and go through the lectures again, completing it while following along.
Due: June 9th, 11:59PM on Blackboard.
Correlation (5 questions, 1 point each)
Researchers were interested in studying the associations between factors that influence GRE scores. After collecting data, the researchers conducted Pearson correlations to answer the following three hypotheses. Below is the output from the analysis. Interpret the output and answer the questions below.
H1: Verbal subscore of the GRE is positively associated with 1st year graduate GPA.
H2: Analytic subscore of GRE is associated with 1st year graduate GPA.
H3: Quantitative subscore on the GRE is associated with 1st year graduate GPA.
H4: Verbal subscore of the GRE is associated with analytic subscore of GRE.
H5: Analytic subscore of GRE is associated with quantitative subscore of GRE.
H1: Verbal subscore of the GRE is positively associated with 1st year graduate GPA.
1) r = ____, p_________. Is this a significant relationship? If so, interpret the relationship below (i.e., write one sentence explaining what the association between the two variables means.
H2: Analytic subscore of GRE is associated with 1st year GPA.
1) r =_____, p______. Is this a significant relationship? If so, interpret the relationship below (i.e., write one sentence explaining what the association between the two variables means.
H3: Quantitative score on the GRE is associated with 1st year graduate GPA.
1) r = ____, p ________. Is this a significant relationship? If so, interpret the relationship below (i.e., write one sentence explaining what the association between the two variables means.
H4: Verbal subscore of the GRE is associated with analytic subscore of GRE.
1) r = ____, p ________. Is this a significant relationship? If so, interpret the relationship below (i.e., write one sentence explaining what the association between the two variables means.
H5: Analytic subscore of GRE is associated with quantitative subscore of GRE.
1) r = ____, p ________. Is this a significant relationship? If so, interpret the relationship below (i.e., write one sentence explaining what the association between the two variables means.
Regression (2 questions, each question is worth 2.5 points)
Folks in the graduate studies admissions office for State University wanted to better understand how students’ quantitative GRE score predicts their 1st year GPA during graduate school. To do this, they gathered data about how students scored on the quantitative portion of the GRE and their GPAs during their first year of graduate school, ran a bivariate regression analysis using SPSS and got the output below. The folks in the admissions office aren’t familiar with interpreting what the findings mean, though, so they’ve enlisted your help to interpret the data. Interpret the data below and answer each of the following questions.
1. What is the b for quantitative subscore of GRE? b =_________, p
If this is a significant predictor, interpret the beta weight below. Make sure to explain if it is a significant predictor AND if it is a positive or negative predictor of 1st year GPA.
2. If a student has a quantitative subscore of GRE of 0.741, then what will their 1st year GPA be? Use the regression formula to answer this question. Regression formula: y = bx + a
Model Summary
.621
a
.386
.380
.48228
Model
1
R
R Square
Adjusted
R Square
Std. Error of
the Estimate
Predictors: (Constant), Quantitative subscore of GRE
a.
ANOVA
b
14.769
1
14.769
63.498
.000
a
23.492
101
.233
38.261
102
Regression
Residual
Total
Model
1
Sum of
Squares
df
Mean Square
F
Sig.
Predictors: (Constant), Quantitative subscore of GRE
a.
Dependent Variable: 1st yr grad gpa -- criterion variable
b.
Coefficients
a
.634
.340
1.865
.065
4.641E-03
.001
.621
7.969
.000
(Constant)
Quantitative
subscore of GRE
Model
1
B
Std. Error
Unstandardized
Coefficients
Beta
Standardized
Coefficients
t
Sig.
Dependent Variable: 1st yr grad gpa -- criterion variable
a.
