Project #45834 - statdisk movies

 

1.      Open the file MOVIES using menu option Datasets and then Elementary Stats, 9th Edition.  This file contains some information about a collection of movies. How many observations are there in this file?

 

252

2.      Analyze the data in this file and complete the following table, indicating for each variable what type of data it represents.

 

Variable

Qualitative/ Quantitative

Discrete/ Continuous/ Neither

Level of Measurement

Rating

qualitative

Neither

PG-R

Budget

quantitative

Discrete

0.325-200

Gross

quantitative

Continuous

20.1-600,743

Length

quantitative

Continuous

93-222

Viewer

qualitative

Discrete

4.3-9.1

3.      Would you consider this data to represent a sample or a population?

A population because there is a measurable characteristic called parameters

 

 

 

Part II. ScatterPlots

 

4.      Create a scatterplot for the data in the Budget and Gross columns. Paste it here.

 

5.      Explain the visual relationship between Budget costs and Gross Earnings of the movies.

Positive trend noted which is non-linear. A lot of scatter noted across plot until 120 on the X axis.

6.      Create a scatterplot for the data in the Budget and the Viewer Rating columns

 

7.      Explain the visual relationship between Budget costs and Viewer Rating.

 

Non-linear trend noted, there is a negative association. As one varible gets larger the other gets smaller. The relationship is weak with a lot of scatter.

 

 

 

 

Part III.  Correlation

 

8.      Using Stat Disk, calculate the linear correlation between the data in the Budget and Gross columns.

 

Correlation Results:

Correlation coeff, r: 0.3991266

Critical r ±0.3291108

P-value (two-tailed): 0.01589

 

 

9.      Explain the mathematical relationship between Budget costs and Gross Earnings of the movies based on the linear correlation coefficient.  Be certain to include comments about the magnitude and the direction of the correlation

 

 

10.  List the sample size and the degrees of freedom for this computation. 

Sample size, n:     36

Degrees of freedom: 34

 

11.  Using Stat Disk, calculate the linear correlation between the data in the Budget and Viewer Rating columns.

 

12.  Compare and contrast these two relationships:

 

BUDGET and GROSS

 

BUDGET and RATING

 

How are they similar? How are they different?

 

[Hint: Read Page 290 “Types of Correlation”]

 

 

 

 

Part IV.  Simple Regression

 

Let’s say that we wanted to be able to predict the GROSS earnings (in millions of dollars) for an upcoming movie based on the BUDGET (in millions of dollars) spent on the movie.  Using this sample data, perform a simple-regression to determine the line-of-best fit. Use the BUDGET as your x (independent) variable and GROSS as your y (response) variable.

 

 

 

  1. Paste your results here:

 

 

 

 

 

Answer the following questions related to this simple regression

 

 

 

14.   What is the equation of the line-of-best fit?  Insert the values for bo and b1 from above.

 

15.  What is the slope of the line?  What does it tell you about the relationship between the BUDGET and GROSS data? Be sure to specify the proper units.

 

[Hint:  remember that both variables are measured in millions of dollars.]

 

16.  What is the y-intercept of the line?  What does it tell you about the relationship between the BUDGET and GROSS data?

 

 

17.  What would you predict for the GROSS earnings of a movie for which the BUDGET is 35?

 

18.  Let’s say you run out of money making the movie and you have to reduce your BUDGET by 5.   What effect would you predict this would have on the GROSS earnings of the movie? 

 

19.  Find the coefficient of determination (R2 value) for this data.  What does this tell you about this relationship?

[Hint:  see definition on Page 311.]

 

 

 


 

 

Part V.  Multiple Regression

 

Let’s say that we wanted to be able to predict the GROSS earnings (in millions of dollars) for an upcoming movie based on three variables:

 

 

 

  • BUDGET (in millions of dollars) spent on the movie

  • LENGTH (in minutes) of the movie

  • VIEWER RATING

     

    Using this sample data, perform a multiple-regression using BUDGET, GROSS, LENGTH, and VIEWER RATING.  Select GROSS (Column 5) as your Dependent variable.

     

 

  1. Paste your results here:

     

 

 

 

 

 

21.  What is the equation of the line-of-best fit?  The form of the equation is Y = bo + b1X1 + b3X3 + b4X4 (fill in values for bo, b1, b3, and b4).

[Round coefficients to 2 decimal places.]

 

22.  What would you predict for the GROSS earnings of a movie for which

 

·         BUDGET is 35

·         LENGTH is 130

·         VIEWER RATING is 7.5

 

 

23.  What is the R2 value for this regression?  What does it tell you about the regression?

 

 

Subject Mathematics
Due By (Pacific Time) 11/02/2014 12:00 am
Report DMCA
TutorRating
pallavi

Chat Now!

out of 1971 reviews
More..
amosmm

Chat Now!

out of 766 reviews
More..
PhyzKyd

Chat Now!

out of 1164 reviews
More..
rajdeep77

Chat Now!

out of 721 reviews
More..
sctys

Chat Now!

out of 1600 reviews
More..
sharadgreen

Chat Now!

out of 770 reviews
More..
topnotcher

Chat Now!

out of 766 reviews
More..
XXXIAO

Chat Now!

out of 680 reviews
More..
All Rights Reserved. Copyright by AceMyHW.com - Copyright Policy