A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y)

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A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).

 

The results of the regression were:

y=ax+b
a=-0.683
b=30.146
r2=0.481636
r=-0.694

 

Use this to predict the number of situps a person who watches 9 hours of TV can do (to one decimal place)

 

QUESTION2

Annual high temperatures in a certain location have been tracked for several years. Let X

represent the year and Y the high temperature. Based on the data shown below, calculate the regression line (each value to two decimal places).

 

y =  x + 

 

x y

3 1.9

4 4.1

5 4.1

6 3.1

7 6.1

8 7.2

9 4.7

 

QUESTION3

Shane is investigating how long his phone's battery lasts (in hours) for various brightness levels (on a scale of 0-100). His data is displayed in the table

Brightness Level (x) 16 16 20 32 43 45 45 74

Hours (y) 4.7 6.1 5.3 5.6 5.2 5.6 4.7 2.8 10

a) Find the equation for the line of best fit. Keep at least 4 decimals for each parameter in the equation.   

b) Interpret the slope in context.

• Shane should expect -0.0377 hours per brightness level.
• Shane should expect -0.0377 brightness level per hour.

c) What does the equation predict for the number of hours the phone will last at a brightness level of 45?

 hours

 

QUESTION4

Run a regression analysis on the following data set, where y

 is the final grade in a math class and x is the average number of hours the student spent working on math each week.

hours/week Grade

X Y

7 67.8

8 62.2

11 73.4

11 76.4

13 74.2

15 87

15 77

19 100

19 96.6

19 100

 

 

State the regression equation

 y=m⋅x+b

with constants accurate to two decimal places.

  

 

What is the predicted value for the final grade when a student spends an average of 11 hours each week on math?

Grade = 

 Round to 1 decimal place.

 

QUESTION5

An experiment is run. The mass of an object is recorded over time.

 

Time (min) Mass (g)

15 47

26 34

32 28

37 19

48 17

 

Using your calculator, run a linear regression to determine the equation of the line of best fit. Round to two decimal places, use x for the variable.

y=

  

 

Using your equation, estimate the mass of the object at 27 minutes.

 

 --------- grams