-Please see the below data from Excel Data Analysis: Please analysis the above d

Question

-Please see the below data from Excel Data Analysis:

Please analysis the above data. I need this analysis to include the following:

-Evaluation using the F and t statistics

-Discussion and analysis of the slope, y intercept, and regression equation

-Discussion of the hypothesis and conclusions based on your analysis..

PLEASE DISCUSS ALL OF THE ABOVE, NOT SOME OF THE ABOVE, ALL OF THE ABOVE.

PLEASE BE AS DETAIELED AS POSSIBLE! USE BOTH PLAIN AND PRECISE LANGUAGE.

THANK YOU!

950920 87328245167 552421193 064121246 02728677280 18157195775282211 723873 853561 788989 5657 59 11900587454168 18135758 0288288 1 4 4 4 6 8 3 2 82684319346 22011010 1 2 2 3 0 0 2 3 2 5 3 1 4 5 5 5 777 91385 0 3 2 2 93899 12256 1 8112 0 311 8359 9002 111000000100000100111110111 2 6 5 5 81322 12345 123 0123456 -11111111122222222222222222

Explanation / Answer

Evaluation using the F and t statistics ?

F = [Regression SS/(k-1)] / [Residual SS/(n-k)]

SS is nothing but sum of square

Here in the above example F value is 37.2325. How we evaluate F value with degree of freedom and sum of square?

F = (24361.6006/3)/(4798.265833/22) = 37.2326

t stat:

Column "t Stat" gives the computed t-statistic for H0: ?j = 0 against Ha: ?j ? 0.

The first t stat calcualation is

=28.82797498/9.559386909

= 3.015671952

Discussion and analysis of the slope, y intercept, and regression equation

The most useful part of this section is that it gives you the linear regression equation:
y = mx + b.
y = slope * x + intercept.
For the above table, the equation would be approximately:

calcualting from coefficient only

y = 28.82+8.94*X1+0.05*X2+12.39*X3

Discussion of the hypothesis and conclusions based on your analysis..

- Hypothesis Testing in a Linear Regression: using 'p-values'

- The p-value associated with the calculated F-statistic is probability beyond the calculated value. Comparing this value with 5%, for example, indicates rejection of the null hypothesis.

The p-value for each term tests the null hypothesis that the coefficient is equal to zero (no effect). A low p-value (< 0.05) indicates that you can reject the null hypothesis. and if P > 0.05 indicated that you do not reject null hypothesis

- Significance F: The significance associated P-Value.

P value = 8.53 , P> 0.05 significance level, so do not reject the null hypothesis

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