Reference no: EM132461581

Visit the NASDAQ historical prices . First, set the date range to be for exactly 1 year ending on the Monday that this course started. click on the blue dates after "Time Period". Next, click the "Apply" button. Next, click the link on the right side of the page that says "Download Data" to save the file to your computer.

Use only use the Close values. Assume that the closing prices of the stock form a normally distributed data set. Do NOT count the number of data points.

1. b) What the mean and Standard Deviation (SD) of the Close column in your data set?
2. c) If a person bought 1 share of Google stock within the last year, what is the probability that the stock on that day closed at less than the mean for that year? Hint: You do not want to calculate the mean to answer this one. The probability would be the same for any normal distribution.
3. If a person bought 1 share of Google stock within the last year, what is the probability that the stock on that day closed at more than $1150?
4. If a person bought 1 share of Google stock within the last year, what is the probability that the stock on that day closed within $50 of the mean for that year? (between 50 below and 50 above the mean)
5. If a person bought 1 share of Google stock within the last year, what is the probability that the stock on that day closed at less than $950 per share. Would this be considered unusal? Use the definition of unusual from the course textbook that is measured as a number of standard deviations
6. At what prices would Google have to close in order for it to be considered statistically unusual? You will have a low and high value. Use the definition of unusual from the course textbook that is measured as a number of standard deviations.
7. What are Quartile 1, Quartile 2, and Quartile 3 in this data set? Use Excel to find these values. This is the only question that you must answer without using anything about the normal distribution.
8. Is the normality assumption that was made at the beginning valid? Why or why not? Hint: Does this distribution have the properties of a normal distribution as described in the course textbook? Real data sets are never perfect, however, it should be close. One option would be to construct a histogram.Something in the range of 10 to 12 classes is a good number.