Please use attached excel file- question 1 tab 1, Question 2 tab 2
Question 1: Bivariate analysis
Copy the dataset under the first tab, labelled Question 1, into a new Microsoft Excel workbook.
What is a stock market index?
A stock market is a collection of selected stocks, also called shares, and the related market index is computed from the prices of these stocks. Indices can be classified in various ways, the most common of which is by performance.
Examples of performance-based indices are the American Standard & Poors 500 (S&P 500), the British Financial Times Stock Exchange 100 (FTSE 100), and the Japanese Nikkei 225. The FTSE 100, for example, is a share index of the 100 companies listed on the London Stock Exchange that have the highest market capitalisation (as capitalisations change over time, the composition of these leading 100 companies is periodically reviewed).
Stock prices often correlate with the stock market index and tend to change as the market index changes. Investigate the relationship between the market index and each of the two stock prices included in the dataset, by following these steps:
Determine the explanatory and response variables.
Run a regression analysis for each of the two stock prices against the index price.
Interpret the results by answering the following questions:
Plot each of the two stocks against the market index on a scatterplot. Include these scatterplots in your submission. What are the expected correlations that might exist between each of the stocks and the market index?
What are the calculated correlation coefficients? Compare these to your plots. Were your initial expectations correct?
Comment on the coefficients of determination. Which of the two models has the higher explanatory power?
What are the beta coefficients for each of the two stocks?
Suppose you were to purchase one of these two stocks, and your decision relied on their volatility in relation to the market index (i.e. their beta coefficients); which of the two stocks would you purchase if you were interested in buying a volatile stock?
(Max. 200 words)
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Question 2: Multivariate analysis
Copy the dataset under the second tab, labelled Question 2, into a new Microsoft Excel workbook.
Sales figures are usually related to more than one variable, whether it is marketing expenditure, advertising material, shelf placement, or product pricing structures. In this question, total sales figures were found to have a correlation with marketing expenditure and the price of the product. Logically, it could be argued that an increase in marketing expenditure should result in an increase in sales. Similarly, an increase in product price could reduce sales figures.
Using the data provided, perform the following analysis:
Determine the explanatory and response variables.
Run a multivariate regression analysis on all three variables.
Interpret the results by answering the following questions:
What is the calculated correlation coefficient? Do the sales figures correlate with the marketing expenditure and price?
Comment on the coefficient of determination. What percentage of the response data can be explained by the explanatory variables?
Determine the multiple regression line equation in the form:
= (intercept) + (coefficient) marketing + (coefficient) price
Using the regression equation formulated, what is the amount of expected sales (in pounds), if the price is set at ?3.50 and the amount spent on marketing is ?300?
Interpret the variables in the regression equation. What impact does each of the factors (marketing and price) have on the sales figures?
(Max. 200 words)
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Requirements: Max 200 words per questions
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