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I need someone to interpret these results on regression analyst

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I need someone to interpret these results on regression analyst and write about 125-150 words stating those results and summerizing the chart.

Research question: Is there a correlation between the account balances and the amount of ATM transactions.

Ho: The regression model is a good fit.
H1: The regression model is not a good fit.
Significance level = 0.05
Decision rule: Reject Ho if the p-value < 0.05


Regression Analysis

r² 0.503 n 60
r 0.709 k 1
(syx) Std. Error 3.056 Dep. Var. Y

ANOVA table
Source SS df MS F p-value
Regression (NNN) NNN-NNNN 1 (NNN) NNN-NNNN 58.59 2.33E-10
Residual (NNN) NNN-NNNN 58 9.3368
Total 1,088.6000 59


Regression output confidence interval
variables coefficients std. error t (df=58) p-value 95% lower 95% upper
Intercept 2.6486 1.0746 2.465 .0167 0.4975 4.7997
X1 0.0051 0.0007 7.655 2.33E-10 0.0038 0.0064

abozer :

Hi, could you please post this table in a more organized version.

abozer :

You can upload the original question on www.sendspace.com and post the download link here.

abozer :

thanks, XXXXX XXXXX better.

Customer :

no problem

Customer :

I need this pretty fast and will up the price to $50 if you think you can have it done quickly.

abozer :

don't worry. I'm writing you right now.

abozer :

The regression equation is y = 2.686 + 0.0051X1

abozer :

We can interpret this as follows,

abozer :

the amount of ATM transactions increases by 0.0051 for every dollar increase in account balance.

abozer :

This is a good fit because the p-value is 2.33E-10 and this value is almost equal to zero.

abozer :

Actually the null and alternative hypothesis are given incorrect.

abozer :

It should be,

abozer :

Ho: The regression model is not a good fit

abozer :

H1: The regression model is a good fit

abozer :

p-value is less than the significance level of 0.05. Based on this we reject the null hypothesis and conclude that the regression model is a good fit.

abozer :

There is significant correlation between the account balance and the number of ATM transactions.

abozer :

r^2 is equal to 0.503 in the output. This means that the regression model explains 50.3% of the variation in the number of ATM transactions by the variation in account balances.

abozer :

r = 0.709. The value of correlation coefficient is positive so there is positive correlation between the account balances and the number of ATM transactions. This means that the number of ATM transactions increase as the account balance increases or the number of ATM transactions decrease as the account balance decreases.

abozer :

(you can skip this one if it is too long) Confidence intervals can be interpreted as follows,

abozer :

We are 95% confident (sure) that the intercept of the regression model is between 0.4975 and 4.7997. Intercept represents the number of ATM transactions when account balance is zero.

abozer :

We are 95% confident that the slope of the regression model is between 0.0038 and 0.0064. Slope represents the increase in the number of ATM transactions for a unit increase in account balance.

abozer :

The rest of the numbers on the Regression output are not worth interpreting.

abozer :

Please let me know if you have any questions.

Customer :

I believe this should be good!

Customer :

Do I just hit the accept button? (Sorry this is my first time using this site)

abozer :

I don't know what the user interface looks like but I guess yes.

abozer :

The accept button should do it.

Customer :

alrighty then, thank you very much.

abozer :

you're welcome.

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