Question

In: Statistics and Probability

A student used multiple regression analysis to study how family spending (y) is influenced by income...

A student used multiple regression analysis to study how family spending (y) is influenced by income (x1), family size (x2), and additions to savings (x3). The variables y, x1, and x3 are measured in thousands of dollars. The following results were obtained.

Anova
df ss
regression 3 45.9634
residual 11 2.6218
Total
coefficient Standard error
intercept 0.0136
x1 0.7992 0.074
x2 0.2280 0.190
x3 -0.5796 0.920

Calculate the estimated regression equation for the relationship between the variables,coefficient of determination. What can you say about the strength of this relationship,Carry out a test to determine whether y is significantly related to the independent variables and Carry out a test to see if x3 and y are significantly related.

Use a 5% level of significance.

.

Solutions

Expert Solution

Sol:

Estimated regression eq uation is

y^=0.0136+0.7992*x1+0.2280*x2-0.5796*x3

,coefficient of determination=R sq=1-ss reg/ ss total

=1-(45.9634/48.5852)

= 0.9460371

=0.9460371*100

=94.60% avriation in y is expolained by model

R sq=0.9560

r=sqrt(0.9560)

= 0.9777525

There exists a strong positive relationship between y and indpeendent variable

Carry out a test to determine whether y is significantly related to the independent variables

Ho:beta1=beta2=beta3=0

Ha:atleast one of the betai is not =0

alpha=0.05

F=MS regressssion/MS residual

MS regresssion=SS regression/df

=45.9634/3

=15.32113

MS residual=Ss residual/df residual

=2.6218/11

=0.2383455

F=15.32113/0.2383455

F= 64.28118

p value in excel=

=F.DIST.RT( 64.28118,3,11)

=2.93051E-07

p value=0.000000293

p<0.05

Reject Ho

Accept Ha

Cocnlsuion:

There is suffcient statistical evidence at 5% level of significance to conclude

there is arelationship between y and independent variables that y is significantly related to the independent variables (x1,x2,x3)

Carry out a test to see if x3 and y are significantly related.

Ho:beta3=0

Ha:beta3 not =0

alpha=0.05

t stat=coeffcient/standard error

=-0.5796/0.920

=-0.63

df=n-k-1=15-3-1=11

=T.DIST.2T(0.63,11)

=0.54155995

p value>0.05

Fail to reject Ho

Accept Ho

There is no suffcient statistical evidence at 5% level of significance to conclude that y and x3 are related

x3 is not a significant variable in predicting y

-0.5796 0.920

Related Solutions

A student used multiple regression analysis to study how family spending (y) is influenced by income...
A student used multiple regression analysis to study how family spending (y) is influenced by income (x1), family size (x2), and additionsto savings(x3). The variables y, x1, and x3 are measured in thousands of dollars. The following results were obtained. ANOVA df SS Regression 3 45.9634 Residual 11 2.6218 Total Coefficients Standard Error Intercept 0.0136 x1 0.7992 0.074 x2 0.2280 0.190 x3 -0.5796 0.920 a. Write out the estimated regression equation for the relationship between the variables. (1 mark) b....
Question 3 (10 marks) A student used multiple regression analysis to study how family spending (y)...
Question 3 A student used multiple regression analysis to study how family spending (y) is influenced by income (x1), family size (x2), and additions to savings (x3). The variables y, x1, and x3 are measured in thousands of dollars. The following results were obtained. ANOVA df SS Regression 3 45.9634 Residual 11 2.6218 Total Coefficients Standard Error Intercept 0.0136 x1 0.7992 0.074 x2 0.2280 0.190 x3 -0.5796 0.920 Write out the estimated regression equation for the relationship between the variables....
Questions 16-23 A multiple linear regression was used to study how family spending ( y) is...
Questions 16-23 A multiple linear regression was used to study how family spending ( y) is influenced by income ( x 1), family size ( x 2), and additions to savings ( x3). The variables y, x 1, and x 3 are measured in thousands of dollars per year. The following results were obtained. ANOVA DF SS Regression    42.450 Residual 11 2.141 Total Coefficients Standard Error Intercept 0.012 x 1 0.742 0.071 x 2 0.201 0.186 x 3 -0.540...
Multiple regression analysis was used to study how an individual's income (Y in thousands of dollars)...
Multiple regression analysis was used to study how an individual's income (Y in thousands of dollars) is influenced by age (X1 in years), level of education (X2 ranging from 1 to 5), and the person's gender (X3 where 0 =female and 1=male). The following is a partial result of a computer program that was used on a sample of 20 individuals. Coefficient    Standard Error              X1 0.6251 0.094              X2 0.9210 0.190              X3 -0.510 0.920 Analysis of Variance...
Multiple regression analysis was used to study the relationship between a dependent variable, y, and four...
Multiple regression analysis was used to study the relationship between a dependent variable, y, and four independent variables; x1, x2, x3, and x4. The following is a partial result of the regression analysis involving 31 observations. Coefficients Standard Error Intercept 18.00 6.00 x1 12.00 8.00 x2 24.00 48.00 x3 -36.00 36.00 x4 16.00 2.00 ANOVA df SS MS F Regression 125 Error Total 760 a) Compute the multiple coefficient of determination. b) Perform a t test and determine whether or...
Describe how simple linear regression analysis and multiple regression are used to support areas of industry...
Describe how simple linear regression analysis and multiple regression are used to support areas of industry research, academic research, and scientific research.
Question C [SD1: 5 Marks]             A multiple regression analysis between yearly income (Y in $1,000s),...
Question C [SD1: 5 Marks]             A multiple regression analysis between yearly income (Y in $1,000s), college grade point average (X1), age of the individuals (X2), and the gender of the individual (X3; zero representing female and one representing male) was performed on a sample of 10 people, and the following results were obtained. Coefficients Standard Error Intercept   4.0928 1.4400     X1 10.0230 1.6512     X2   0.1020 0.1225     X3 -4.4811 1.4400 ANOVA DF SS MS F Regression 360.59 Residual...
A multiple regression analysis between yearly income (y in thousands of dollars), college grade point average...
A multiple regression analysis between yearly income (y in thousands of dollars), college grade point average (X1), age of the individuals (X2 in years), and the gender of the individual (X3: 0 representing female and 1 representing male) was performed on a sample of 10 people, and the following results were obtained. Coefficients Standard of Error Intercept 4.0928 1.4400 x1 10.0230 1.6512 x2 0.1020 0.1225 x3 -4.4811 1.4400 ANOVA Source of Variation DF Sum of Squares Mean Square F Regression...
Multiple Regression Analysis was used to find out which X variable have relationship with my Y...
Multiple Regression Analysis was used to find out which X variable have relationship with my Y variable (reduce overspending on food and beverage), and how strong relationship is.FIT A FIRST ORDER AUTO AGGRESSIVE MODEL (AR(1) USING Y(T) AS THE RESPONSE VARIABLE Y (T-1) AS THE INPUT VARIABLE. RECORD THE REGRESSION EQUATION. CALCULATE THE EXPONENTIAL SMOOTHING MODELS AND CALCULATE A MOVING AVERAGE MODEL. 4-Mar $31.69 5-Mar $4.19 5-Mar $19.01 5-Mar $7.99 6-Mar $3.32 6-Mar $57.11 7-Mar $4.07 8-Mar $2.49 8-Mar $6.30...
The owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (y)...
The owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x 1) and newspaper advertising (x2). The estimated regression equation was Weekly Gross Revenue ($1000s) Televison Advertising ($1000s) Newspaper Advertising ($1000s) 96 5 2.5 90 3 3 96 5 1.5 92 3.5 2.5 96 4 4.3 94 4.5 2.3 95 3.5 5.2 95 4 3.5 ลท = 76.3 + 3.41 x 1 + 1.33 x 2 The computer...
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT