The data shown below are the initial weights and gains in weight (in grams) of female rats on a high protein diet from 24 to 84 days of age. The point of interest in these data is whether the gain in weight is related to (dependent on) the initial weight. If so, then feeding experiments on female rats can be made more precise by adjusting for differences in initial weights of the rats. Statistically test this with a regression analysis. Rat NumberInitial Weight (gms)Weight Gain (gms)1501282641593761584641195741336601127699686812695613210481181157107125910613468214451031565104I used excel's regression took pak and got the following: SUMMARY OUTPUT Regression Statistics Multiple R0.489416452 R Square0.239528464 Adjusted R Square0.181030653 Standard Error8.869929833 Observations15 ANOVA dfSSMSFSignificance F Regression1322.1498151322.154.094660.064078516 Residual131022.78351878.6757 Total141344.933333 CoefficientsStandard Errort StatP-valueLower 95%Upper 95%Lower 95.0%Upper 95.0%Intercept33.3096386613.419838352.482120.02754.31784051662.30143684.31784051662.3014368Weight Gain (gms)0.2251011890.1112420622.023530.06408-0.015222670.46542505-0.0152226750.46542505I do not know how to word Ho and Ha. Is the p and t values for weight gain or intercept?***What is the equation for the multiple regression?***What is the best estimate of the amount of variance in Y which is due to its regression on the independent variables?

The independent variable is Initial Weight. The dependent variable is Weight Gain. This is simple…

Answered: The data shown below are the initial…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The data shown below are the initial weights and gains in weight (in grams) of female rats on a high protein diet from 24 to 84 days of age. The point of interest in these data is whether the gain in weight is related to (dependent on) the initial weight. If so, then feeding experiments on female rats can be made more precise by adjusting for differences in initial weights of the rats. Statistically test this with a regression analysis.

Rat Number	Initial Weight (gms)	Weight Gain (gms)
1	50	128
2	64	159
3	76	158
4	64	119
5	74	133
6	60	112
7	69	96
8	68	126
9	56	132
10	48	118
11	57	107
12	59	106
13	46	82
14	45	103
15	65	104

I used excel's regression took pak and got the following:

SUMMARY OUTPUT

Regression Statistics
Multiple R	0.489416452
R Square	0.239528464
Adjusted R Square	0.181030653
Standard Error	8.869929833
Observations	15

ANOVA
	df	SS	MS	F	Significance F
Regression	1	322.1498151	322.15	4.09466	0.064078516
Residual	13	1022.783518	78.6757
Total	14	1344.933333

	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	33.30963866	13.41983835	2.48212	0.0275	4.317840516	62.3014368	4.317840516	62.3014368
Weight Gain (gms)	0.225101189	0.111242062	2.02353	0.06408	-0.01522267	0.46542505	-0.015222675	0.46542505