10) A battery manufacturer is developing a new battery to be used for the iPhone 10. Before they will switch to the new design, they need to verify that the new battery will outperform (measured as hours of continuous music play) the current battery. a) State the Hypothesis to show the new battery design has longer playing time than the current battery design. b) Choose a level of a. Use a = 0.05 for this problem. c) To test the hypothesis, the battery manufacturer tests 30 iPhone 7s with the new battery design and 30 iPhone 10s with the current battery design. The data appear in the iPhone worksheet of the HW1 data workbook on Moodle. Collect data and calculate necessary statistics to test the hypothesis. d) Sketch the sampling distribution. Include the critical value and test statistic e) Draw a conclusion and report that in the problem context. f) Calculate the p-value for the hypothesis test g) Use Excel to perform the hypothesis test.
New | Current |
13.3 | 14.2 |
16.4 | 12.9 |
13.9 | 14.5 |
15.4 | 14.9 |
15.1 | 15 |
14.6 | 15.1 |
14.9 | 13.2 |
17.2 | 14 |
14.2 | 15.1 |
17.3 | 13.8 |
14.8 | 15.4 |
16.3 | 15.8 |
16 | 15.9 |
15.5 | 16 |
15.8 | 14.1 |
18.1 | 14.9 |
12.8 | 13.7 |
15.9 | 12.4 |
13.4 | 14 |
14.9 | 14.4 |
14.6 | 14.5 |
14.1 | 14.6 |
14.4 | 12.7 |
16.7 | 13.5 |
13.7 | 14.6 |
16.8 | 13.3 |
14.3 | 14.9 |
15.8 | 15.3 |
15.5 | 15.4 |
15 | 15.5 |
10) A battery manufacturer is developing a new battery to be used for the iPhone 10....
Consider the viscosity sample data presented in class, You learn from your client that her viscosity specification is between 12.5 cs and 17.5 cs. What percentage of batches do you expect to be “out of spec”? 13.3 14.5 15.3 15.3 14.3 14.8 15.2 14.5 14.6 14.1 14.3 16.1 13.1 15.5 12.6 14.6 14.3 15.4 15.2 16.8 14.9 13.7 15.2 14.5 15.3 15.6 15.8 13.3 14.1 15.4 15.2 15.2 15.9 16.5 14.8 15.1 17 14.9 14.8 14 15.8 13.7 15.1 13.4...
The following data are product weights for the same items produced on two different production lines. Test for a difference between the product weights for the two lines. Use . Line 1 Line 2 13.7 14.1 13.7 14.7 13.0 13.9 14.4 13.9 13.3 13.8 13.3 15.0 13.5 13.6 13.4 14.6 13.6 14.0 14.0 13.7 14.9 13.6 What is the value of the test statistic? Enter negative value as negative number. (to 2 decimals) What is the -value for the hypothesis...
can u clearly show me how to find a sample size (N) , A2, and can you also tell me why we are using an X Chart? Problem 1 A restaurant wants to control kitchen preparation time of dinner meals using an X chart. The process standard deviation is unknown. Each evening a manager takes a random sample of 14 dinner orders and measures and records their kitchen preparation time. Create an X Chart using data in the table below...
7.Physical Characteristics of sharks are of interest to surfers and scuba divers as well as to marine researchers. Because it is difficult to measure jaw width in living sharks, researchers would like to determine whether it is possible to estimate jaw width from body length, which is more easily measured. The following data on x = length (in feet) and y = jaw width (in inches) for 44 sharks was found in various articles appearing in the magazines Skin Diver...
R programming: MPG GPM WT DIS NC HP ACC ET 16.9 5.917 4.360 350 8 155 14.9 1 15.5 6.452 4.054 351 8 142 14.3 1 19.2 5.208 3.605 267 8 125 15.0 1 18.5 5.405 3.940 360 8 150 13.0 1 30.0 3.333 2.155 98 4 68 16.5 0 27.5 3.636 2.560 134 4 95 14.2 0 27.2 3.676 2.300 119 4 97 14.7 0 30.9 3.236 2.230 105 4 75 14.5 0 20.3 4.926 2.830 131 5 103 ...
A gardener plants 300 sunflower seeds (of a brand called KwikGrow) and, after 2 weeks, measures the seedlings’ heights (in mm). These heights are recorded below. He is interested in testing whether the mean height of sunflowers grown from KwikGrow seeds is greater than 33 mm two weeks after planting. He decides to conduct a hypothesis test by assuming that the sampling distribution of the sample mean has a normal distribution. For the purposes of this question, you may assume...
R programming: MPG GPM WT DIS NC HP ACC ET 16.9 5.917 4.360 350 8 155 14.9 1 15.5 6.452 4.054 351 8 142 14.3 1 19.2 5.208 3.605 267 8 125 15.0 1 18.5 5.405 3.940 360 8 150 13.0 1 30.0 3.333 2.155 98 4 68 16.5 0 27.5 3.636 2.560 134 4 95 14.2 0 27.2 3.676 2.300 119 4 97 14.7 0 30.9 3.236 2.230 105 4 75 14.5 0 20.3 4.926 2.830 131 5 103 ...
A major oil company has developed a new gasoline additive that is supposed to increase mileage. To test this hypothesis, ten cars are randomly selected. The cars are driven both with and without the additive. The results are displayed in the following table. Can it be concluded, from the data, that the gasoline additive does significantly increase mileage? Let d = (gas mileage with additive)-(gas mileage without additive). Use a significance level of a = 0.01 for the test. Assume...
R programming: MPG GPM WT DIS NC HP ACC ET 16.9 5.917 4.360 350 8 155 14.9 1 15.5 6.452 4.054 351 8 142 14.3 1 19.2 5.208 3.605 267 8 125 15.0 1 18.5 5.405 3.940 360 8 150 13.0 1 30.0 3.333 2.155 98 4 68 16.5 0 27.5 3.636 2.560 134 4 95 14.2 0 27.2 3.676 2.300 119 4 97 14.7 0 30.9 3.236 2.230 105 4 75 14.5 0 20.3 4.926 2.830 131 5 103 ...
A major oil company has developed a new gasoline additive that is supposed to increase mileage. To test this hypothesis, ten cars are randomly selected. The cars are driven both with and without the additive. The results are displayed in the following table. Can it be concluded, from the data, that the gasoline additive does significantly increase mileage? Let d = (gas mileage with additive)-(gas mileage without additive). Use a significance level of a = 0.01 for the test. Assume...