Go To This Website First, Set The Date Range To The Beginnin

Go Tothis Website First Set The Date Range To Begin Exactly 1 Year B

Go to this website. First, set the date range to begin exactly 1 year before the start of the term and to end with the day before the Monday that this course started. For example, if the course started on August 12, 2013, set the date range from August 12, 2012, through August 11, 2013. Next, click the link on the right that says "Download to Spreadsheet," and save the file to your computer. This project will only use the closing values. Assume that the closing prices of the stock form a normally distributed data set. This means that you need to use Excel to find the mean and standard deviation and then use those numbers and the methods you learned in sections 5.2 and 5.3 of our textbook for normal distributions to answer the questions. Complete this assignment within a single Excel file. Show your work or explain how you obtained each of your answers. Answers with no work and no explanation will receive no credit.

Paper For Above instruction

This assignment focuses on analyzing the stock prices of Google over a specified one-year period, leveraging statistical methods related to normal distribution. The goal is to interpret historical closing prices to understand probability and data distribution characteristics, applying Excel as the main analytical tool. The process begins with data collection, where the student is instructed to set specific date ranges and download relevant stock data, emphasizing the importance of the closing prices as the primary dataset for analysis. The subsequent steps involve calculating descriptive statistics such as mean and standard deviation, fundamental to understanding the behavior of stock prices within the assumed normal distribution framework.

The first question asks for the probability that a randomly selected closing price from the last year was below the mean, emphasizing the symmetry of the normal distribution. As per properties of the normal distribution, this probability should be 0.5, because by definition, the probability of a value being less than the mean in a normal distribution is 50%. This question tests conceptual understanding rather than calculation, expecting a student to recognize the symmetry property inherent to normal distributions and to justify answer accordingly.

Next, the assignment addresses the probability that the stock closed above $500. This requires calculating the z-score for $500 using the mean and standard deviation obtained from the data, and then using standard normal distribution tables or Excel functions to find the corresponding probability. The calculation involves: z = (x - mean) / standard deviation. Subsequently, the probability of the stock closing at more than $500 is 1 minus the cumulative probability up to $500 (i.e., P(X > 500) = 1 - P(Z ≤ z)). Given the variability of stock prices, this probability is typically small, reflecting the rarity of such high closing prices in normal market conditions.

The third question asks for the probability that the stock’s closing value was within $45 of the mean, meaning between (mean - 45) and (mean + 45). This involves calculating two z-scores, one for (mean - 45) and another for (mean + 45). The cumulative probabilities corresponding to these z-scores are then subtracted to find the probability that a closing price fell within this range.

In the fourth question, we analyze the probability that the stock closed at $362.50 or less on a randomly selected day. This requires computing the z-score for $362.50 and then finding the cumulative probability up to this value in the standard normal distribution. It effectively asks for the percentile rank of $362.50 within the dataset.

The fifth question explores what prices would be considered statistically unusual, defined as being beyond 2 standard deviations from the mean in either direction (per the empirical rule). Specifically, the student must find the lower and upper bounds: mean - 2×std dev and mean + 2×std dev, which are typically regarded as thresholds for unusual observations.

Question six involves calculating quartiles (Q1, Q2, Q3) directly from the dataset using Excel functions such as QUARTILE or QUARTILE.INC. Since quartiles are based on the data distribution, this step does not assume normality and provides a non-parametric view of the data’s central tendency and variability.

Finally, the seventh question assesses whether the assumption of normality holds. Students are encouraged to evaluate this by constructing a histogram of the closing prices, assessing its shape, symmetry, and skewness. A roughly bell-shaped, symmetric histogram suggests the data approximately follows a normal distribution, whereas noticeable skewness, kurtosis, or deviations indicate departure from normality.

References

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