(a) Find the 5-number summary for the difference of arthritic pain levels. Minimum = Q₁ = Median Q3 = Maximum = (b) One of the conditions for inference for population mean difference of paired data is normality. Outliers within a data set cast a shadow of doubt upon the normality of the population distribution. Use the 5-number summary calculated part (a) to determine if there are any outliers in the data set. Which of the values, any, is an outlier according to the outlier rule? (Select all that apply.) -6 -2 02 03 Onone of the data values are outliers (c) Despite your answer to part (b), assume the conditions for inference have been met. Using the sample standard deviation, s=2.18, calculate a 95% confidence interval for the true mean difference of arthritic pain levels. (Use a table or technology. Round your answers to two decimal places.) (d) What would happen if the scientists increased the sample size? Continue to assume that the conditions for inference have been met. Using the sample standard deviation of s= 2.18, and the same point estimate, calculate a 95% confidence interval for the true mean difference of arthritic pain levels if a sample size of 30 were used. (Use a table or technology. Round your answers to two decimal places.) 1.[

It is widely claimed that a histogram is skewed to the left when the median is greater than the mean and to the right when the median is less than the mean. But there are exceptions to this claim. Demonstrate this exception by creating a data set that has at least 15 samples and plot the histogram.

1. The two plots have similar distrubutions. Are the distrubutions skewed left, approximtly symmetric, or skewed right? 2. Which is greater, the mean or the median, within each plot? Why does this make snese, gicen the type of distrubution you identified in the first part? 3. The population has drastically declined over recent years. Does the data show a difference in bee prefrence towards high quality hives versus how quality hives? Usse statistical evidennce to support your response.

True or false. If the IQR of a dataset is 0 then any observation smaller than Q1 is classified as an outlier using the 1.5(IQR) rule.

What is a data set outlier? Why is it important to identify outliers in a data set?

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

What is the slope of the median median line for the dataset in this table?

For a box plot, here are 4 values at the low end of a dataset and 4 values near the high end of a set of dataset: 18, 18, 18, 18 ... 23, 23, 25, 25, ... If the lower fence or boundary for outlier determination is 16 and the upper fence or boundary is 24, what value would you connect the whisker to on the high side of the "box?"

Exercise 6. Below is a box plot of life expectancy in years for 142 countries in 2007. Life Expectancy (years) 80 70 60 50 40 (a) Using the box plot, estimate Q1, the median, Q3, and the IQR. Also, are there any potential outliers? (b) What characteristics of the distribution are apparent in the histogram, but not in the box plot? 2

Describe the natures of the two distributions (uniform, normal, skewed left, skewed right), and identify possible outliers.