Using test data on 20 types of laundry detergent, an analyst fitted a regression to predict CostPerLoad(average cost per load in cents per load) using binary predictors TopLoad(1 if washer is a toploading model, 0 otherwise) and Powder(if detergent was in powder form, 0 otherwise). Interpret the results. (Data are from Consumer Reports 68, no. 8 [November 2003], p. 42) R2
0.117
Adjusted R2
0.006
n
19
R
0.341
k
2
Std. Error
5.915
Dep. Var.
Cost Per Load
ANOVA table
Source
SS
df
MS
F
p-value
Regression
73.8699
2
36.9350
1.06
.3710
Residual
559.8143
16
34.9884
Total
633.6842
18
Regression output
confidence interval
variables
coefficients
std. error
t(df= 16)
p-value
95% lower
95% upper
Intercept
26.0000
4.1826
6.216
1.23E-05
17.1333
34.8667
Top-Load
−6.3000
4.5818
−1.375
.1881
−16.0130
3.4130
Powder
−0.2714
2.9150
−0.093
.9270
−6.4509
5.9081