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The output from Excel containing data bars appears below. These are good candidates for carriers to use in the future. The relative frequency of D is 1. If the total sample size is the frequency of D is 0.

These data are categorical. The cellular phone providers had the highest number of complaints.

The percentage frequency distribution shows that the two financial industries banks and collection agencies had about the same number of complaints. Also, new car dealers and cable and satellite television companies also had about the same number of complaints. Suburb living is steady, but the trend would be that living in the city would decline while living in small towns and rural areas would increase. Class Frequency 2 8 11 10 9 Total: 40 b.

Class Relative Frequency Percent Frequency 0. Class Frequency Cumulative Frequency 10 10 14 24 17 41 7 48 2 50 Class Frequency 1 3 6 10 7 2 1 0 12 10 8 6 4 2 0 b.

The distribution is slightly skewed to the right. The most common score for students is between and No student scored above , and only 3 students scored above Only 4 students scored below Because the additional data point, 12, is lower than the mean and median computed in part a, we expect the mean and median to decrease. In other words, the 20th percentile is the value in position 1 15 plus 0.

The mode is the most often occurring value which is 53 because 53 appears three times in the data set, or use the Excel function MODE.

SNGL because there is only a single mode in this data set. To find the mean annual growth rate, we must use the geometric mean.

So the mean annual growth rate is 0. Next, we calculate g So the mean annual return for the Stivers mutual fund is 1. While the Stivers mutual fund has generated a nice annual return of 7. To calculate the median, we first sort all 48 commute times in ascending order.

Because there are an even number of values 48 , the median is between the 24th and 25th largest values. The 24th largest value is The values MULT function. In Excel, we can find this value using the function VAR. The third quartile is the 75th percentile of the data. However, in our date the values in both the 36th and 37th positions are Therefore, the 75th percentile is The mean waiting time for patients with the wait-tracking system is The mean waiting time for patients without the wait-tracking system is The standard deviation of waiting time for patients with the wait-tracking system is 9.

The standard deviation of waiting time for patients without the wait-tracking system is Wait times for patients with the wait-tracking system are substantially shorter than those for patients without the wait-tracking system.

However, some patients with the wait-tracking system still experience long waits. The median number of hours worked for science teachers is The median number of hours worked for English teachers is The box plots show that science teachers spend more hours working per week than English teachers. The box plot for science teachers also shows that most science teachers work about the same amount of hours; in other words, there is less variability in the number of hours worked for science teachers.

The standard deviation of waiting time for patients without the wait-tracking system is Wait times for patients with the wait-tracking system are substantially shorter than those for patients without the wait-tracking system.

However, some patients with the wait-tracking system still experience long waits. The median number of hours worked for science teachers is The median number of hours worked for English teachers is The box plots show that science teachers spend more hours working per week than English teachers.

The box plot for science teachers also shows that most science teachers work about the same amount of hours; in other words, there is less variability in the number of hours worked for science teachers.

Recall that the mean patient wait time without wait-time tracking is Recall that the mean patient wait time with wait-time tracking is As indicated by the positive z—scores, both patients had wait times that exceeded the means of their respective samples. Even though the patients had the same wait time, the z—score for the sixth patient in the sample who visited an office with a wait tracking system is much larger because that patient is part of a sample with a smaller mean and a smaller standard deviation.

The z—scores for all patients follow. In other words, we expect that 0. There appears to be a negative linear relationship between the x and y variables. Without Excel, we can use the calculations shown below to calculate the covariance: S function. The negative covariance confirms that there is a negative linear relationship between the x and y variables in this data set. To calculate the correlation coefficient without Excel, we need the standard deviation for x and y: Then the correlation coefficient is calculated as: The correlation coefficient indicates a strong negative linear association between the x and y variables in this data set.

The scatter chart indicates that there may be a positive linear relationship between profits and market capitalization. Without Excel, we can use the calculations below to find the covariance and correlation coefficient: C32 to calculate the covariance, which is This indicates that there is a positive relationship between profits and market capitalization. C32 to calculate the correlation coefficient, which is 0. This indicates that there is a strong linear relationship between profits and market capitalization.

Without Excel, we can use the calculations below to find the correlation coefficient: The correlation coefficient indicates that there is a moderate positive linear relationship between jobless rate and delinquent loans.

If the jobless rate were to increase, it is likely that an increase in the percentage of delinquent housing loans would also occur. Heavenly Chocolates Website Traffic 1. Descriptive statistics for the time spent on the website, number of pages viewed, and amount spent are shown below. The following histogram demonstrates that the data are skewed to the right.

Histogram of Time min 14 12 10 Frequency 8 6 4 2 0 5 10 15 20 25 30 Time min The mean number of pages viewed during a visit is 4. The following histogram indicates that the data are skewed to the right. Histogram of Amount 10 8 Frequency 6 4 2 0 20 40 60 80 Amount 2. However, the sample size for each day of the week are very small, with only Friday having more than ten transactions. We would suggest a larger sample size be taken before recommending any specific stratgegy based on the day of week statistics.

This result would suggest targeting special promotion offers to Firefox users or users of other types of browsers. But, before recommending any specific strategies based upon the type of browser, we would suggest taking a larger smaple size. A scatter diagram showing the relationship between time spent on the website and the amount spent follows: The sample correlation coefficient between these two variables is. The scatter diagram and the sample correlation coefficient indicate a postive relationship between time spent on the website and the total amount spent.

Thus, the sample data support the conclusion that customers who spend more time on the website spend more. A scatter diagram showing the relationship between the number of pages viewed and the amount spent follows: Solutions to Case Problems The sample correlation coefficient between these two variables is.

The scatter diagram and the sample correlation coefficient indicate a postive relationship between time spent on the website and the number of pages viewed. Thus, the sample data support the conclusion that customers who view more website pages spend more. A scatter diagram showing the relationship between the number of pages viewed and the time spent on the website follows: The scatter diagram and the sample correlation coefficient indicate a postive relationship between the number of pages viewed and the time spent on the website.

And, consideration should also be given to developing marketing strategies based upon possible differences in sales associated with the day of the week as well as differences in sales associated with the type of browser used by the customer. Download pdf. Remember me on this computer. Enter the email address you signed up with and we'll email you a reset link. Need an account? Click here to sign up.