The Regression Equation Suppose in this semester, our Exam 1 average was about 85 with an SD of about 12. Suppose the correlation between our Exam 1 and Exam 2 scores will be similar to what it has been in the past, about 0.6, and finally, suppose our Exam 2 scores will be similar to previous semesters' Exam 2 scores with an average of 82 and a SD of 8.2. Use this information to answer the following questions: What is the slope of the regression equation for predicting our Exam 2 scores from Exam 1 scores? Round to 3 decimal places.

0.410

Step-by-step explanation:

We are predicting exam 2 scores from exam 1 scores so the dependent variable y is exam 2 scores and independent variable is exam 1 scores x.

The regression equation is

y=a+bx

Where y is exam 2 scores and x is exam 1 scores.

We are given that

correlation coefficient=r=0.6.

Mean and standard deviation of x are xbarx=85 and Sx=12.

Mean and standard deviation of y are xbary=82 and Sy=8.2.

The slope b for this scenario can be found as

Thus, the slope of the regression equation for predicting  Exam 2 scores from Exam 1 scores is 0.410.

the data of the detroit pistons in numerical order from least to greatest is 0.30, 0.37, 0.55, 0.62, 0.69, 0.72, 0.73, 0.75, 0.77, 0.78, 0.80, 0.81, 0.81, 0.83, 0.84, 0.89

the data of the miami heat in numerical order from least to greatest is 0.50, 0.50, 0.56, 0.57, 0.67, 0.72, 0.72, 0.72, 0.75, 0.75, 0.76, 0.81, 0.82, 0.90, 1.00, 1.00

the detroit pistons median : 1.52

the miami heat median: 1.47

the iqr of this data is 0.05

answer: 10 meter

step-by-step explanation:

need details