Question

In: Statistics and Probability

10.Find the least squares regression equation for predicting per capita income using the percentage of high school graduates.

  1. Questions 10 through 15 refer to the following:

    The following data concerning income and educational attainment for several counties in Alabama were taken from the U.S. Census Website.

    County

    % High School Grads

    Per Capita Income

    Autauga

    87.6

    26168

    Chilton

    80.1

    22045

    Coosa

    72.9

    18080

    Dallas

    79.0

    17611

    Elmore

    86.8

    24711

    Jefferson

    89.0

    28162

    Lee

    88.7

    24951

    Lowndes

    74.8

    18434

    Macon

    80.5

    18385

    Montgomery

    85.5

    26255

    Pike

    80.0

    20180

    Shelby

    91.6

    34117

    Sum

    996.5

    279,099

    Sum of Squares

    83,144.21

    6,772,411,831

    ∑xy

    23,475,084.2

     

    10.Find the least squares regression equation for predicting per capita income using the percentage of high school graduates.

       

    y = 419082.121 - 57.439x

       

    y = -39729.72 + 758.510x

       

    y = -6652.046 + 317.053x

       

    y = -18096.537 + 474.365x

       

    y = 22417.029 + 127.884x

 

QUESTION 11

  1. Find the sample correlation coefficient between per capita income and percentage of high school graduates.

 

QUESTION 12

  1. Find the value of the t statistic for testing H0: β1 = 0 vs. HA: β1 ≠ 0.

 

QUESTION 13

  1. What's the p-value for the test statistic in #12?

 

QUESTION 14

  1. Do the data provide significant evidence at the .05 level of a linear relationship between per capita income and the percentage of high school graduates?

       

    yes

       

    no

       

    12

       

    robot

 

QUESTION 15

  1. What is the expected change in per capita income associated with a 1% increase in the proportion of high school graduates?

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