# Applied Management Statistics

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Formalities:

• Wordcount: No more than 1000 words. All questions should be answered.
• Font: Arial 12,5 pts.
• Text alignment: Justified.
• The in-text References and the Bibliography have to be in Harvard’s citation style.

Submission: Sunday, 9th  of May, Time: 23:55.

It assesses the following learning outcomes:

• Ability to use regression analysis with real-world financial data
• Ability to test statistical hypothesis in cases close to reality
• Understand and interpret linear regression equation

Question 1 (50 points):

The quality control manager at a light-bulb factory needs to determine whether the mean life of a large shipment of light bulbs is equal to 375 hours.

The population standard deviation is 100 hours. A random sample of 64 bulbs indicates a sample mean life of 350 hours.

Question 2 (40 points):

Fitting a straight line to a dataset yields the following prediction line:

Question 3 (10 points):

1. Choose any stock of your interest from the US market.
2. Collect stock prices daily data (last 60 trading days, adjusted close price), collect the SP500 index data (last 60 trading days, adjusted close price). You might find useful to get the data from Yahoo Finance.

1. Compute returns for each trading day using the following formula:

Returns_today = (Price_today – Price_yesterday)/Price_yesterday

Do that for your stock of interest as well as for the SP500 index.

1. Run a regression of stock returns on SP500 returns.
2. The coefficient of SP500 returns, we will call in finance beta coefficient computed using market model. Interpret beta of your stock.

You might find this link useful: https://www.investopedia.com/terms/b/beta.asp#types-of-beta-values

Pages (550 words)
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