1. Setup: The attendance at a racetrack (r) and the amount that was bet (y) on n = 10 selected days are given in the following table: Attendance x (hundreds) 119 130 121 120 134 133 126 125 132 128 Amount Bet y (millions of dollars) 2.1 3.2 2.6 2.2 3.3 3.9 2.8 2.7 3.4 3.5 Other statistics from our data: = 126.8 S₂ = 5.514 Saz = 273.6 Say = 26.54 ÿ = 2.97 Sy = 0.585 Syy = 3.081 Regression Line Equation: ŷ= -9.33+0.097 (a) Using the data above, calculate the residuals for each ŷ, i= 1,2, ..., 10 and provide the residual values. (3 decimals are fine.) (b) Do the residuals appear to come from a normal distribution? Use either a Q-Q Plot and/or the Shapiro-Wilk Test (using a = 0.05). Provide your plot and/or the results of the test. (c) Suppose we assume that the error variance is equal to 0.36, i.e. ² = 0.36. Find a 95% confidence interval for ₁.

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1. Setup: The attendance at a racetrack (r) and the amount that was bet (y) on n = 10
selected days are given in the following table:
Attendance x
(hundreds)
119
130
121
120
134
133
126
125
132
128
Amount Bet y
(millions of dollars)
2.1
3.2
2.6
2.2
3.3
3.9
2.8
2.7
3.4
3.5
Other statistics from our data:
* = 126.8
S₂ = 5.514
Szz =
= 273.6
Szy = 26.54
y = 2.97
Sy = 0.585
Syy = 3.081
Regression Line Equation:
ŷ = -9.33 +0.097z
(a) Using the data above, calculate the residuals for each ĝi, i = 1,2,..., 10 and provide
the residual values. (3 decimals are fine.)
(b) Do the residuals appear to come from a normal distribution? Use either a Q-Q Plot
and/or the Shapiro-Wilk Test (using a = 0.05). Provide your plot and/or the results
of the test.
(c) Suppose we assume that the error variance is equal to 0.36, i.e. 2 = 0.36. Find a
95% confidence interval for 3₁.
Transcribed Image Text:1. Setup: The attendance at a racetrack (r) and the amount that was bet (y) on n = 10 selected days are given in the following table: Attendance x (hundreds) 119 130 121 120 134 133 126 125 132 128 Amount Bet y (millions of dollars) 2.1 3.2 2.6 2.2 3.3 3.9 2.8 2.7 3.4 3.5 Other statistics from our data: * = 126.8 S₂ = 5.514 Szz = = 273.6 Szy = 26.54 y = 2.97 Sy = 0.585 Syy = 3.081 Regression Line Equation: ŷ = -9.33 +0.097z (a) Using the data above, calculate the residuals for each ĝi, i = 1,2,..., 10 and provide the residual values. (3 decimals are fine.) (b) Do the residuals appear to come from a normal distribution? Use either a Q-Q Plot and/or the Shapiro-Wilk Test (using a = 0.05). Provide your plot and/or the results of the test. (c) Suppose we assume that the error variance is equal to 0.36, i.e. 2 = 0.36. Find a 95% confidence interval for 3₁.
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