Question

In: Statistics and Probability

Consumer Reports provided extensive testing and ratings for more than 100 HDTVs. An overall score, based...

Consumer Reports provided extensive testing and ratings for more than 100 HDTVs. An overall score, based primarily on picture quality, was developed for each model. In general, a higher overall score indicates better performance. The following (hypothetical) data show the price and overall score for the ten 42-inch plasma televisions (Consumer Report data slightly changed here):

Brand

Price (X)

Score (Y)

Dell

2900

50

Hisense

2800

52

Hitachi

2700

45

JVC

3500

60

LG

3300

56

Maxent

2000

30

Panasonic

4200

68

Phillips

3100

56

Proview

2500

35

Samsung

3000

48

Use the above data to develop and estimated regression equation and interpret the coefficients. Compute Coefficient of Determination and correlation coefficient and show their relation. Interpret the explanatory power of the model. Estimate the overall score for a 42-inch plasma television with a price of $3400. Finally, test the significance of the slope coefficient.

Solutions

Expert Solution

x y (x-x̅)² (y-ȳ)² (x-x̅)(y-ȳ)
2900 50 10000.00 0.00 0.00
2800 52 40000.00 4.00 -400.00
2700 45 90000.00 25.00 1500.00
3500 60 250000.00 100.00 5000.00
3300 56 90000.00 36.00 1800.00
2000 30 1000000.00 400.00 20000.00
4200 68 1440000.00 324.00 21600.00
3100 56 10000.00 36.00 600.00
2500 35 250000.00 225.00 7500.00
3000 48 0.00 4.00 0.00
ΣX ΣY Σ(x-x̅)² Σ(y-ȳ)² Σ(x-x̅)(y-ȳ)
total sum 30000 500 3180000 1154.0 57600.00
mean 3000.00 50.00 SSxx SSyy SSxy

sample size ,   n =   10          
here, x̅ = Σx / n=   3000.00   ,     ȳ = Σy/n =   50.00  
                  
SSxx =    Σ(x-x̅)² =    3180000.0000          
SSxy=   Σ(x-x̅)(y-ȳ) =   57600.0          
                  
estimated slope , ß1 = SSxy/SSxx =   57600.0   /   3180000.000   =   0.0181
                  
intercept,   ß0 = y̅-ß1* x̄ =   -4.3396          
                  
so, regression line is   Ŷ =   -4.3396   +   0.0181   *x

................

intercept : -4.3396

if x= 0, then the score (Y) will be - 4.3396

slope = 0.0181

if x is increase by 1 unit, score (Y) will be increased by 0.0181

.........................

correlation coefficient ,    r = Sxy/√(Sx.Sy) =   0.9508
      

cofficient of determination ,R² =    (Sxy)²/(Sx.Sy) =    0.9041
cofficient of determination = (correlation cofficient )2

....................

Predicted Y at X=   3400   is                  
Ŷ =   -4.33962   +   0.018113   *   3400   =   57.245
..............

slope hypothesis test               tail=   2
Ho:   ß1=   0          
H1:   ß1╪   0          
n=   10              
alpha =   0.05              
estimated std error of slope =Se(ß1) = Se/√Sxx =    3.720   /√   3180000.00   =   0.0021
                  
t stat = estimated slope/std error =ß1 /Se(ß1) =    0.0181   /   0.0021   =   8.6840
                  
t-critical value=    2.306   [excel function: =T.INV.2T(α,df) ]          
Degree of freedom ,df = n-2=   8              
p-value =    0.0000              
decison :    p-value<α , reject Ho              
Conclusion:   Reject Ho and conclude that slope is significantly different from zero              

..............

Please revert back in case of any doubt.

Please upvote. Thanks in advance.


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