Suppose the following data are product weights for the same items produced on two different production lines. Line 1 Line 2 13.1 13.4 13.9 14.7 14.0 14.6 13.5 14.0 13.3 14.1 13.6 13.2 13.8 14.3 13.1 14.9 12.5 14.2 14.3 14.8   15.0   14.5 A. Test for a difference between the product weights for the two lines. Use α = 0.05. State the null and alternative hypotheses. 1. H0: The two populations of product weights are identical.     Ha: The two populations of product weights are not identical. 2. H0: Median      for line 1 − Median for line 2 ≤ 0     Ha: Median for line 1 − Median for line 2 > 0     3. H0: Median for line 1 −         Median for line 2 < 0     Ha: Median for line 1 − Median for line 2 = 0 4. H0: The two populations of      product weights are not identical.     Ha: The two populations of product weights are identical. 5.  H0: Median for       line 1 − Median for line 2 ≥ 0      Ha: Median for line 1 − Median for line 2 < 0 B. Find the value of the test statistic. W =  Find the p-value. (Round your answer to four decimal places.) p-value =    C. State your conclusion. 1. Reject H0. There is not sufficient evidence to conclude that there is a significant difference between the product weights for the two lines. 2. Do not reject H0. There is sufficient evidence to conclude that there is a significant difference between the product weights for the two lines.    3. Reject H0. There is sufficient evidence to conclude that there is a significant difference between the product weights for the two lines. 4. Do not reject H0. There is not sufficient evidence to conclude that there is a significant difference between the product weights for the two lines.

HOME Realty claims that it can sell a detached, residential house faster than any other realty company. With the aim of examining HOME's claim, you sample 20 customers who sold a detached, residential house through HOME and record the selling times (in days) of the houses. Your data are summarized in the following histogram. Relative frequency 0.4- 0.3 0.35 0.20 0.2+ 0.20 0.15 0.10 0.1- 0.0- 0 10 20 30 Selling time (in days) 40 50 Based on the histogram, find the proportion of selling times in the sample that are at least 20 days. Write your answer as a decimal, and do not round your answer. 0 × 5

A certain manufacturing company has the following data on quantities shipped and unit costs for each of its four products. Mean Shipping Cost per Unit ($) Base-Period Quantities (Year 1) Products Year 1 Year 5 A 1,500 10.50 15.90 B 5,000 16.25 33.00 6,000 12.20 17.40 D 2,500 20.00 35.50 Use the price data to compute a Paasche index for the shipping cost if year 5 quantities are 4,500, 3,000, 7,000, and 3,000 for products A, B. C. and D, respectively. (Round your answer to the nearest integer.)

Why can’t the following mode predict 100% of the variability in the price of a used Corolla?

To test whether the mean time needed to mix a batch of material is the same for machines produced by three manufacturers, the Jacobs Chemical Company obtained the following data on the time (in minutes) needed to mix the material.    Manufacturer   1 2 3     25 34 15     31 32 14     29 37 18     27 33 17 a. Use these data to test whether the population mean times for mixing a batch of material differ for the three manufacturers. Use a = 0.05.  Sum of squares, treatment =  Sum of squares, error =  Mean squares, treatment =  mean squares, error =  Calculate the value of the test statistic (to 2 decimals). The P-value is:  Less than 0.01, between 0.01 and 0.025, between 0.025 and 0.05, between 0.05 and 0.10, greater than 0.10 What is your conclusion? b. At the a = 0.05 level of significance, use Fisher's LSD procedure to test for the equality of the means for manufacturers 1 and 3. What conclusion can you draw after carrying out this test?

To determine if their 14 oz filling machine is properly adjusted, Harvey Soft Drinks has decided to use an X-Chart which uses the range to estimate the variability in the sample. J. Answer How to enter your answ Table Step 1 of 7: What is the Center Line of the control chart? Round your answer to three decimal places. Control Chart Period 1 2 3 4 5 6 7 8 9 10 11 Select the Copy Table button to copy all values. To select an entire row or column, either click on the row or column header or use the Shift and arrow keys. To find the average of the selected cells, select the Average Values button. Copy Table Average Values The average of the selected cell(s) is 14.000. Copy Value Sample Mean Sample Range 14.0060 0.04 0.04 0.04 0.10 0.08 0.09 0.07 0.05 0.05 0.06 0.07 obs1 obs2 obs3 obs4 obs5 14.00 13.99 14.03 14.01 14.00 14.02 14.05 14.05 14.01 14.04 14.0340 14.02 14.01 14.05 14.04 14.02 14.0280 14.04 13.97 14.05 13.95 14.00 14.0020 13.96 14.01 14.00 14.04 14.02 14.0060 13.96 14.00 14.00…

6. Accidents on highways are one of the main causes of death or injury in developing countries and the weather conditions have an impact on the rates of death and injury. In foggy, rainy, and sunny conditions, 1/4, 1/8, and 1/21 of the accidents result in death, respectively. Sunny conditions occur 60% of the time, while rainy and foggy conditions each occur 20% of the time. Given that an accident without deaths occurred, what is the conditional probability that it was foggy at the time?

1. A study of the relation between the waistline and percent body fat in men yielded the data shown (waistline measurement in inches). waistline (x) 34.7 46.5 32.8 41.3 29.8 39.3 35.7 29.0 percent fat (y) 21.8 33.6 13.4 27.1 13.7 30.2 18.5 11.2 x = 36.1375 y = 21.1875 SSxx = 248.53875 SSay = 332.67375 SSyy = 494.30875 (a) Find the proportion of the variability in percent body fat that is accounted for by the size of the waistline. Explain fully. (b) Find the regression line for predicting y from x. (c) Construct a 95% confidence interval for the average percent body fat of all men whose waistline size is 34.0 inches. (d) test HO: Beta1 is 0 vs. Ha : Beta1 is not 0, compute the appropriate test statistic and p-value, then make your decision at a = 0.05. (e) Construct a 90% confidence interval for beta1. (f) Compute a 90% confidence interval for the average percent fat when waistline is 35.

10. The following data was collected from 1 bag of Hershey Kisses®. Each Kiss® was weighed in grams with the wrapper and recorded in the table below. Hershey cims that there are 368 grams of chocolate in one bag.     Hershey Kiss Weights in Grams 4.76 4.72 4.74 4.55 4.91 4.74 4.78 4.71 4.80 4.78 4.78 4.75 4.79 4.82 4.91 4.83 4.68 4.74 4.70 4.80 4.70 4.76 4.70 4.83 4.93 4.74 4.84 4.82 4.76 4.77 4.72 4.78 4.83 4.75 4.74 4.68 4.84 4.71 4.71 4.76 4.66 4.78 4.73 4.74 4.92 4.77 4.80 4.79 4.86 4.64 4.78 4.70 4.75 4.78 4.76 4.83 4.66 4.77 4.83 4.78 4.69 4.81 4.68 4.78 4.88 4.72 4.85 4.85 4.81 4.74 4.80 4.82 4.84 4.70 4.85 4.70 4.81 4.72 4.79 4.73 4.61   How might standard deviation and the shape of the distribution indicate how consistent Hershey® is in the manufacturing of their Kisses®?

The estimated labor cost associated with a particular proposal is based on the number of plantings of trees, shrubs, and so on to be used for the project. For cost-estimating purposes, managers use two hours of labor time for the planting of a medium-sized tree. Actual times from a sample of 10 plantings during the past month follow (times in hours). 1.6 1.5 2.6 2.3 2.5 2.3 2.6 3.0 1.3 2.3 What is the test statistic? (Round your answer to three decimal places.) What is the p-value? (Round your answer to four decimal places.) p-value =