Q1-Q5: a) Find the value of the line ar correlation coefficient r b) Find the critical values ofr from table A-6 using x= 0.05 c) Determine whether there is sufficient evidence to support a claim of a linear correlation Between the two variables. d) Find the regression equation, e) Letting the first variable be the predictor (x) variable, find the indicated predicted value. Q1. Altitude and Temperature: Altitude 3 10 14 22 28 31 33 (thousands of feet) Temperature OF) 57 37 -5 -30 -41 -54 24

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Q1-Q5:
a) Find the value of the line ar correlation coefficient r
b) Find the critical values ofr from table A-6 using x= 0.05
c) Determine whether there is sufficient evidence to support a claim of a linear correlation
Between the two variables.
d) Find the regression equation,
e) Letting the first variable be the predietor (x) variable, find the indicated predieted value.
Q1. Altitude and Temperature:
Altitude
3
10
14
22
28
31
33
( thousands of feet)
Temperature
( °F)
57
37
24
-5
-30
-41
-54
At 6.327 thousand feet, the author recorded the temperature. Find the best predieted temperature
at that altitude. How does the result compare to the actual recorded value of 48°F?
Transcribed Image Text:Q1-Q5: a) Find the value of the line ar correlation coefficient r b) Find the critical values ofr from table A-6 using x= 0.05 c) Determine whether there is sufficient evidence to support a claim of a linear correlation Between the two variables. d) Find the regression equation, e) Letting the first variable be the predietor (x) variable, find the indicated predieted value. Q1. Altitude and Temperature: Altitude 3 10 14 22 28 31 33 ( thousands of feet) Temperature ( °F) 57 37 24 -5 -30 -41 -54 At 6.327 thousand feet, the author recorded the temperature. Find the best predieted temperature at that altitude. How does the result compare to the actual recorded value of 48°F?
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