Question 2 The following regression output was obtained. The regression model is Test scores on student teacher ratio. When your research assistant cut and pasted the results for you, there were several vital pieces of information missing. See output below: SUMMARY OUTPUT Regression Statistics Multiple R 0.226362751 R Square (a) Adjusted R Square 0.048970335 Standard Error 18.5809675 Observations 420 ANOVA df SS MS F Regression 1 7794.110041 7794.110041 22.57511055 Residual 418 144315.4836 345.2523531 Total 419 (b) Coefficients Standard Error t Stat P-value Intercept 698.9329523 9.467491444 str -2.279808287 0.479825567 (c) (d) STR stands for student teacher ratio. In your local school district, the STR is 25 students to 1 teacher. In another less affluent area, class sizes are much larger with an STR of 35. Predict the test scores of the two school districts
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Question 2
The following regression output was obtained. The regression model is Test scores on
student teacher ratio. When your research assistant cut and pasted the results for you, there
were several vital pieces of information missing. See output below:
SUMMARY
OUTPUT
Regression Statistics
Multiple R 0.226362751
R Square (a)
Adjusted R Square 0.048970335
Standard Error 18.5809675
Observations 420
ANOVA
df SS MS F
Regression 1 7794.110041 7794.110041 22.57511055
Residual 418 144315.4836 345.2523531
Total 419 (b)
Coefficients
Standard
Error t Stat P-value
Intercept 698.9329523 9.467491444
str -2.279808287 0.479825567 (c)
(d) STR stands for student teacher ratio. In your local school district, the STR is 25 students to 1 teacher. In another less affluent area, class sizes are much larger with an STR of 35. Predict the test scores of the two school districts
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