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Chi - Squared and Anova I was provided with the solutions or what the problem sh

ID: 3182639 • Letter: C

Question

Chi - Squared and Anova

I was provided with the solutions or what the problem should solve to but still lost. Please help. Thank you!

Ull, llse the data to estirate izs 20. The following data refer to the number of deaths per 10,000 adults in a large Eastern city in the different seasons for the years 1982 to 1986. Year Winter Spring Summer Fall 1982 33.6 31.4 29.8 32.1 1983 32.5 30.1 28.5 29.9 1984 35.3 33.2 29.5 28.7 1985 34.4 28.6 33.9 30.1 1986 37.3 34.1 28.5 29.4 (a) Assuming a two-factor model, estimate the parameters. (b) Test the hypothesis that death rates do not depend on the season. Use the 5 percent level of significance. (c) Test, at the 5 percent level of significance, the hypothesis that there is no effect due to the year.

Explanation / Answer

Answer:

MINITAB USED:

a).

Regression Equation

deaths = 31.545 + 0.180 year_1982 - 1.295 year_1983 + 0.130 year_1984 + 0.205 year_1985 + 0.780 year_1986 - 1.505 season_fall - 0.065 season_spring - 1.505 season_summer + 3.075 season_winter

b).

Analysis of Variance

Source    DF   Adj SS Adj MS F-Value     P-Value

year     4      9.507     2.377        0.57      0.691

season   3   69.949 23.316     5.57      0.012

Error       12 50.213   4.184

Total      19   129.669

To test season effect, calculated F=5.57, P=0.012 which is < 0.05 level of significance.

Ho is Rejected.

Season effect is significant.

c).

To test year effect, calculated F=0.57, P=0.691 which is > 0.05 level of significance.

Ho is Not Rejected.

Year effect is not significant.

General Linear Model: deaths versus year, season

Method

Factor coding (-1, 0, +1)

Factor Information

Factor Type   Levels Values

year    Fixed       5 1982, 1983, 1984, 1985, 1986

season Fixed       4 fall, spring, summer, winter

Analysis of Variance

Source    DF   Adj SS Adj MS F-Value P-Value

year     4    9.507   2.377     0.57    0.691

season   3   69.949 23.316     5.57    0.012

Error     12   50.213   4.184

Total     19 129.669

Model Summary

      S    R-sq R-sq(adj) R-sq(pred)

2.04558 61.28%     38.69%       0.00%

Coefficients

Term        Coef SE Coef T-Value P-Value VIF

Constant 31.545    0.457    68.96    0.000

year

1982     0.180    0.915     0.20    0.847 1.60

1983    -1.295    0.915    -1.42    0.182 1.60

1984     0.130    0.915     0.14    0.889 1.60

1985     0.205    0.915     0.22    0.826 1.60

season

fall    -1.505    0.792    -1.90    0.082 1.50

spring -0.065    0.792    -0.08    0.936 1.50

summer -1.505    0.792    -1.90    0.082 1.50

Regression Equation

deaths = 31.545 + 0.180 year_1982 - 1.295 year_1983 + 0.130 year_1984 + 0.205 year_1985 + 0.780 year_1986 - 1.505 season_fall - 0.065 season_spring - 1.505 season_summer + 3.075 season_winter

Fits and Diagnostics for Unusual Observations

                             Std

Obs deaths    Fit Resid Resid

14   33.90 30.25   3.65   2.31 R

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