The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for five randomly selected middle school students. Using this data, consider the equation of the regression line, y = bo + bjx, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 1 4 Overall Grades 98 91 79 75 72 Table 5. 2.
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.
![The table below gives the number of hours spent unsupervised each day as well as the overall grade
averages for five randomly selected middle school students. Using this data, consider the equation of the
regression line, y = bo + bjx, for predicting the overall grade average for a middle school student based
on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or
may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to
use the regression line to make a prediction if the correlation coefficient is not statistically significant.
4
Hours Unsupervised
Overall Grades
98
91
79
75
72
Table
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Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places.
Answer(How to Enter) 2 Points
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Question 8 -
of 13 Step 1 of 6
The table below gives the number of hours spent unsupervised each day as well as the overall grade
averages for five randomly selected middle school students. Using this data, consider the equation of the
regression line, ŷ = bo + bjx, for predicting the overall grade average for a middle school student based
on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or
may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to
use the regression line to make a prediction if the correlation coefficient is not statistically significant.
Hours Unsupervised
1
4
5
Overall Grades
98
91
79
75
72
Table
Copy Data
Prev
Step 1 of 6: Find the estimated slope. Round your answer to three decimal places.
Next
Answer(How to Enter) 2 Points
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