Multivariate_Regression_1
For the first part of this assignment, I did a multivariate regression. The predictor variable was sales, and the two independent variables were quantity and discounted amount. This section aimed to observe what will happen to sales when the quantity and discount variables are adjusted and observe the relationship between the dependent and independent variables. The regression analysis shows that the test was significant, f (2, 9991) = 214.7341; the p-value of F was zero, which is less than 0.05. Our correlation coefficient is 0.203012, which means the relationship is a weak positive relationship. Increasing both quantity and discount variables will increase the dependent variable.
R squared is 0.041214, a small effect size; our experiment might not have been strong enough to power our experiment. Looking at our p- values in the second part, we see that all our variables are significantly related. For multivariate regression the regression equation is usually y= constant +B1*(X1) + B2*(X2) +…BnXn, used the information from the table and values from the regression table to calculate the value of y and got a positive number.
Multivariate_Regression_2
For the second section, I did a regression analysis for sales, profit, and discounted amounts. Customers like discounts and most companies profit after discounting the original amount. Therefore, companies use discounts as a form of marketing to increase sales. I used sales as my predictor variable and profit and discount as my outcome variable to prove this theory.
From the regression analysis results, r=0.485515, which is a moderate relationship between variables. However, R squared was 0.2357, a small effect size; our sample might have been too small to power our research. The results from the ANOVA analysis show that your experiment is significant F (2,9991) = 1540.76, p=0. Therefore, increasing both variables increases the dependent variable. The p-values also show that our variables are all significantly related.
As stated above, multivariate regression the regression equation is usually y= constant +B1*(X1) + B2*(X2) +…Bn, and the values from the regression and order table were used to calculate the value of Y. One of the independent variables was negative, which reduced the sales compared to when all the variables were positive. Therefore, my hypothesis was true, increasing discount and profit increases the dependent variable- sales.
References
Nussli, N., & Oh, K. (2001, January 1). Intentionality in blended learning design: Applying the principles of meaningful learning, U-learning, UDL, and CRT. IGI Global: International Academic Publisher. https://www.igi-global.com/chapter/intentionality-in-blended-learning-design/258339
Wolters, C. A. (1998). APA PsycNet. APA PsycNet. https://psycnet.apa.org/record/1998-02710-004
Yousef, A. M., & Chatti, M. A. (2014). Academia.edu – Share research. https://www.academia.edu/download/54798183/Video-Based_Learning_A_Critical_Analysis.pdf
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