Question

Write report in the regression analysis as follows. we should create a data about below problems

• Consider any problem in accounting, finance, marketing and management (depend on your subject). As an example, problem: is any relationship between salesof tea bags (y) and price (x1), advertise cost (x2)? Consider sales as dependent variable and price, advertise as independent variables [do not use this example].

• Choose different dependent and independent variables depends on your specialization. (your choice)

• Collect at least 15 observations by your own from any place internet or book. (your choice).

• This is individual report. If you cheat data or your data is the same as another student, your mark will be zero

• Do your analysis in excel.  

Your report must include the following elements

• Variables: what are the dependent and independent variables.

• Problem: what relationship you want to study?

• Data: you must have at least 15 observations in each variable

• Analysis: include analysis in your report

o correlation,

o determination,

o regression

o model test and individual variables test (hypothesis)for regression coefficients (Note: use p-value to take decision or F or t).​

• Explanation the results.

• Conclusion

Answer 1

Solution :-

We will study the Wine Market

Variables :

Dependent Variable - Wine Price

Independent Variables - WinterRain, AGST, HarvestRain, Age

We will study Wine Prices and how the independent variables mentioned above affect the prices of wine.

Data :

Price	WinterRain	AGST	HarvestRain	Age
7.495	600	17.1167	160	31
8.0393	690	16.7333	80	30
7.6858	502	17.15	130	28
6.9845	420	16.1333	110	26
6.7772	582	16.4167	187	25
8.0757	485	17.4833	187	24
6.5188	763	16.4167	290	23
8.4937	830	17.3333	38	22
7.388	697	16.3	52	21
6.7127	608	15.7167	155	20
7.3094	402	17.2667	96	19
6.2518	602	15.3667	267	18
7.7443	819	16.5333	86	17
6.8398	714	16.2333	118	16
6.2435	610	16.2	292	15
6.3459	575	16.55	244	14
7.5883	622	16.6667	89	13
7.1934	551	16.7667	112	12
6.2049	536	14.9833	158	11
6.6367	376	17.0667	123	10
6.2941	574	16.3	184	9
7.292	572	16.95	171	8
7.1211	418	17.65	247	7
6.2587	821	15.5833	87	6
7.186	763	15.8167	51	5

We will look at the correlation betweeen variables, coefficients, regression and p-value

Correlation between dependent variable with each independent variable -

Price and WinterRain
Correlation = 0.1366505

Price and AGST
Correlation = 0.6595629

Price and WinterRain
Correlation = 0.1366505

Price and Age
Correlation = 0.4477679

Regression Analysis :

Formula = Price ~ WinterRain + AGST + HarvestRain + Age

Residuals :
Min 1Q Median 3Q Max
-0.45470 -0.24273 0.00752 0.19773 0.53637

Coefficients :
Estimate Std. Error t value Pr(>|t|)
(Intercept) -3.4299802 1.7658975 -1.942 0.066311 .
WinterRain   0.0010755 0.0005073 2.120 0.046694 *
AGST 0.6072093 0.0987022 6.152 5.2e-06 ***
HarvestRain -0.0039715 0.0008538    -4.652 0.000154 ***
Age   0.0239308 0.0080969    2.956 0.007819 **
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.295 on 20 degrees of freedom
Multiple R-squared: 0.8286, Adjusted R-squared: 0.7943
F-statistic: 24.17 on 4 and 20 DF, p-value: 2.036e-07

Explanation of the analysis :

Price of wine depend on all these independent variables.

AGST and Harvest Rain affects the prices the most, AGST increases the price whereas Harvest Rain decreases the price.

Age also affects significantly and is directly proportional to the prices.

Winter Rains also affects the prices of wine in a significant manner and also directly proportional to the proces.

Conclusion :

Price of wine is dependent on various external factors, some of them are Age, Rains and weather.

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