M03-Activity

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Indiana University, Bloomington *

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S301

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Statistics

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Feb 20, 2024

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STAT-S301 · Applied Statistical Methods for Business · Summer 2023 In-Class Activity M03 Name Group Members 1) 2) 3) 4) 1974 MotorTrend Magazine Dataset Go to Canvas Modules M03 M03 In-Class Activity and download the Excel dataset: mtcars.xlsx . The data was taken from a 1974 issue of the American magazine MotorTrend . It contains 12 variables on 32 different types of vehicles, but for this activity we’ll only be using mpg and wt , the miles per US gallon and the weight (1000lbs), respectively. 1 Z-Scores What is more unusual? A car that weighs more than 5K lbs (5000 lbs) or a car that gets better than 30 miles per gallon? This is a difficult question to answer because we are trying to compare two variables with different units/scales. A way to get around these issues is to compare both on a standardized scale. The most common way of standardizing a value is through the Z-score: Z = x µ σ or Z = x ¯ x s ( µ is the known mean; ¯ x is the mean estimated from data. σ is a known standard deviation; s is the standard deviation estimated from data.) Round your answers to two decimal places for the questions below. The mean wt of the 32 cars is , and the standard deviation of wt is . The mean mpg of the 32 cars is , and the standard deviation of mpg is . Now, if a vehicle is 5000 pounds (5K lbs) and gets 30 miles per gallon, The z-score for the weight would be . The z-score for the miles per gallon would be . Therefore, between the wt and mpg , the value that makes this car more unusual is the . 20.09 6.03 3.22 0.98 wt 1.82 1.64 Jackson Dumas Jackson Dumas No Group Assigned
2 Empirical Rule A common distribution for continuous variables is the normal distribution. This “bell-shaped”distribution is sym- metric with most values falling closer to the mean. We’ll talk more about normal distributions in a few weeks, but for now we can use the empirical rule to calculate some basic probabilities assuming the true distribution of the data is normal. The rule is relatively simple: if the distribution is normal, 68% of all data should fall within one standard deviation of the mean, 95% of all data should fall within two standard deviation of the mean, and 99.7% of all data should fall within three standard deviations of the mean. Answer the following questions assuming the data is normally distributed. Use the mean and standard deviation from the previous section. It may be helpful to compute the z-scores of the values given. What is the probability a vehicle gets between 8.04 and 32.14 miles per gallon? Use symmetry to find the probability a vehicle weighs between 2.24 K lbs and 3.22 K lbs. 3 Percentiles The Excel command to find a percentile is =PERCENTILE.EXC( array , k ) where k is between 1 / ( n +1) and n/ ( n +1) where n is the number of data points. So k is the percentile, like the 80th percentile, written as a decimal, 0.8. For quartiles, there is also the command =QUARTILE.EXC( array , quart) where quart could be 1, 2, or 3 for first, second, or third quartiles. The Excel command to find a percentile rank is =PERCENTRANK.EXC( array , x ,[significance]). This will return the percentile of the value x within the data in array to the number of significant digits specified. If no number of digits is specified, Excel chooses for you. Answer the following questions using the mpg variable. Round your answers to two decimal places. 1. What is the 62 percentile? 2. What is the percentile rank of 23 mpg? 3. What is the 3rd quartile? 4. What is the 2nd quartile? 5. What are three different Excel commands to compute the 2nd quartile? 6. What is the 5-number summary? Round your answer to two decimal places. 4 Submission At the end of class, each individual should submit this worksheet with all sections filled out to Gradescope through Canvas Modules M03 M03 In-Class Activity as practiced last week in Module 02. 93.7% 31.3% 21.18 0.778 22.8 19.2 Median QuartileInc/Exc PercentileInc/Exc Min Max Quartile 1 Median Quartile 3
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