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ANSWER:
EXPLANATION:
As per question given:
a)
x | p | log x |
10 | 67 | 2.302585 |
15 | 79 | 2.70805 |
20 | 82 | 2.995732 |
25 | 88 | 3.218876 |
30 | 95 | 3.401197 |
35 | 98 | 3.555348 |
Using Excel
data -> data analysis -> regression
SUMMARY OUTPUT | |||||
Regression Statistics | |||||
Multiple R | 0.9911 | ||||
R Square | 0.9823 | ||||
Adjusted R Square | 0.9778 | ||||
Standard Error | 1.6941 | ||||
Observations | 6 | ||||
ANOVA | |||||
df | SS | MS | F | Significance F | |
Regression | 1 | 635.3535 | 635.3535 | 221.3816 | 0.0001 |
Residual | 4 | 11.4798 | 2.8699 | ||
Total | 5 | 646.8333 | |||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | |
Intercept | 11.4501 | 4.9803 | 2.2991 | 0.0830 | -2.3774 |
log x | 24.2165 | 1.6276 | 14.8789 | 0.0001 | 19.6976 |
p^ = 11.4501 + 24.2165 ln x
r = 0.9911
b)
when x = 42
p^ = 11.4501 + 24.2165* ln (42)
= 101.9633
= 102 %
this is not correct because the percentage can't be more than 100
this occurs due to extrapolation error as 2022 is outside sample data
predicting for such value may give error which it does
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