6.4.2 Using the data from Exercise 6.1.14 on swim times, a. Find the median and quartiles for the data. b. Make a box plot of the data. c. Repeat (a) and (b) for the data without the extreme outli and comment. d. Compare the distribution of the data with and without t extreme outlier

5:23 Pulse = 101 of ... 3.00-3.79 3.80-4.59 4.60-5.39 5.40-6.19 6.20-6.99 Pulse > 11 5 3 0 1 Chosen classes can vary. Aa 34. Twenty-nine executives reported the number of telephone calls made during a randomly selected week as shown here. Construct a stem and leaf plot for the data and analyze the results. 22 14 12 14 12 9 54 9 54 12 16 12 12 14 49 10 14 8 21 37 28 36 22 9 33 58 31 41 19 3 18 25 28 52 35. The National Insurance Crime Bureau reported that these data represent the number of 51 G

c. Which of the following is the correct graph of the given data? -ОА. 10 1012 12 10 O C. 12- 81012 1012 Using the graph, explain the dramatic difference between the answers to parts (a) and (b). Choose the correct answer below. OA. The point (10,10) is not an outier, but it does have a strong effect on the least squares line and the correlation coefficient. OB. The point (10,10) does not have any effect on the least squares line and the correlation coefficient. OC. The point (10,10) is an outler that has a weak effect on the least squares line and the correlation coefficient. OD. The point (10,10) is an outlier that has a strong effect on the least squares line and the correlation coefficient.

For the dataset below, do a complete box-and-line plot analysis. 3 15 18 19 23 23 26 27 28 29 50 Your work must include:Quartiles: Q1, Q2, Q3Interquartile range (IQR) Upper Limit Lower Limit Adjacent Values Outliers. If you have outliers,you must explain why they are outliers. Don’t forget to draw the box and line plot

Find the following measures of dispersion for the data below: 3 2 1 8 4 17 7 18 14 13 3 3 10 2 20 4 16 Sorted Data Minimum Quartile 1 Median Quartile 3 Maximum Range Interquartile Range

This exercise requires the use of a statistical software package. The cotton aphid poses a threat to cotton crops. The accompanying data on y  =  Infestation rate (aphids/100 leaves) x1  =  Mean temperature (°C) x2  =  Mean relative humidity appeared in an article on the subject. y x1 x2 y x1 x2 62 21.0 57.0 76 24.8 48.0 86 28.3 41.5 94 26.0 56.0 99 27.5 58.0 99 27.1 31.0 105 26.8 36.5 119 29.0 41.0 101 28.3 40.0 75 34.0 25.0 64 30.5 34.0 44 28.3 13.0 28 30.8 37.0 18 31.0 19.0 15 33.6 20.0 22 31.8 17.0 31 31.3 21.0 24 33.5 18.5 68 33.0 24.5 41 34.5 16.0 5 34.3 6.0 22 34.3 26.0 19 33.0 21.0 24 26.5 26.0 43 32.0 28.0 55 27.3 24.5 59 27.8 39.0 60 25.8 29.0 81 25.0 41.0 88 18.5 53.5 76 26.0 51.0 103 19.0 48.0 109 18.0 70.0 96 16.3 79.5 Find the estimated regression equation of the multiple regression model  y = ? + ?1x1 + ?2x2 + e.  (Round your numerical values to two decimal places.)  =        Assess the utility of the…

provide an interpretation of the the plots presented here. what do you learn about the data distribution? do any possible concerns emerge? Then, in two paragraphs, continue with an elaboration on the controlling idea, perhaps with an explanation, implication, or statement about significance.

Are there any mild outliers in the college students data? Show all work. Construct and label a modified boxplot for the college students data.

Two companies produce small motorcycles of varying quality. An important measure of quality is the top speed the motorcycle can obtain on a flat surface. Do the following data provide evidence that the average top speed of cycles from these two companies differ? Report the p-value to two decimal places. Do not assume equal variances.    Top Speed in mph from Company 1 Top Speed in mph from Company 2 21.5 53.0 20.3 40.1 49.6 49.3 43.8 51.6 50.5 52.6 52.5 50.6 47.8   37.0   33.2