A manufacturing company designed a factorial experiment to determine whether the number of defective parts produced by two machines differed and if the number of defective parts produced also depended on whether the raw material needed by each machine was loaded manually or by an automatic feed system.following data give the numbers of defective parts produced.Loading SystemManualAutomatic3030Machine 134262024Machine 22228Use a = 0.05 to test for any significant effect due to machine, loading system, and interaction.Find the value of the test statistic for machine. (Round your answer to two decimal places.)Find the p-value for machine. (Round your answer to three decimal places.)p-value =State your conclusion about machine.O Because the p-value > a = 0.05, machine is not significant.O Because the p-value > a = 0.05, machine is significant.O Because the p-value sa = 0.05, machine is significant.O Because the p-value sa = 0.05, machine is not significant.Find the value of the test statistic for loading system. (Round your answer to two decimal places.)Find the p-value for loading system. (Round your answer to three decimal places.)p-value =State your conclusion about loading system.O Because the p-value s a = 0.05, loading system is significant.O Because the p-value > a = 0.05, loading system is significant.O Because the p-value > a = 0.05, loading system is not significant.O Because the p-value s a = 0.05, loading system is not significant.Find the value of the test statistic for interaction between machine and loading system. (Round your answer to two decimal places.)Find the p-value for interaction between machine and loading system. (Round your answer to three decimal places.)p-value =State your conclusion about interaction between machine and loading system.O Because the p-value > a = 0.05, interaction between machine and loading system is not significant.O Because the p-value s a = 0.05, interaction between machine and loading system is significant.O Because the p-value sa = 0.05, interaction between machine and loading system is not significant.O Because the p-value > a = 0.05, interaction between machine and loading system is significant.

Given information: The data represents waiting time in minutes for rides by loading and unloading…

Answered: A manufacturing company designed a…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A campus researcher wanted to investigate the factors that affect visitor travel time in a complex, multilevel building on campus. Specifically, he wanted to determine whether different building signs (building maps versus wall signage) affect the total amount of time visitors require to reach their destination and whether that time depends on whether the starting location is inside or outside the building. Three subjects were assigned to each of the combinations of signs and starting locations, and travel time in seconds from beginning to destination was recorded. How should the data be analyzed? Wall Signs Map Starting Room Interior 141, 119, 238 85, 94, 126 Randomized block design O Completely randomized design 2 x 2 factorial design Levene's test Exterior 224, 339, 139 226, 129, 130
Basketball players can take shots worth 3 points, 2 points, or 1 point. A scout is assessing two players- Tabitha and Lauren-who play for different teams in different leagues. The scout wonders if they have similar or different shot selections. They take a random sample of Tabitha's games and a separate random sample of Lauren's games. They tally how many of each type of shot the players attempted in those games. Here is a summary and the results of a chi-square test: Chi-square test: Shot vs. player Tabitha Lauren 3-point 8 12 Expected 10.34 9.66 2-point 40 37 Expected 39.83 37.17 1-point 12 Expected 9.83 9.17 x² = 2.097, DF = 2, P-value = 0.350 %3D Assume that all conditions for inference were met. At the a = 0.05 significance level, what is the most appropriate conclusion to draw from this test? Choose 1 answer: This is convincing evidence that the distribution of shot type differs between Tabitha and Lauren.
fill blanks underlines.
The International League of Triple-A minor league baseball consists of 14 teams organized into three divisions: North, South, and West. The data showing the average attendance for the 14 teams in the International League are contained in the Excel Online file below. Also shown are the teams’ records; W denotes the number of games won, L denotes the number of games lost, and PCT is the proportion of games played that were won. Construct a spreadsheet to answer the following questions. Team Name Division W L PCT Attendance Buffalo Bisons North 66 77 0.462 8791 Lehigh Valley IronPigs North 55 89 0.382 8454 Pawtucket Red Sox North 85 58 0.594 9080 Rochester Red Wings North 79 70 0.53 6909 Scranton-Wilkes Barre Yankees North 88 56 0.611 7164 Syracuse Chiefs North 69 77 0.473 5749 Charlotte Knights South 68 78 0.466 4545 Durham Bulls South 74 70 0.514 7020 Norfolk Tides South 64 78 0.451 6269 Richmond Braves South 63 79 0.444 4449 Columbus Clippers West 69 73 0.486…
A college student is interested in whether presoaking time has an effect on cleanliness of clothing. He collects the dirty clothes from all of the people in his dorm and randomly assigns clothing to one of four presoak time conditions: 5 minutes, 10 minutes, 15 minutes, 20 minutes. He then asks members of another dorm to rate the cleanliness of the items (they don’t know which clothing got which soaking time). The data are presented below. C) Perform an LSD test and answer the questions that follow (SHOW ALL WORK!!! This can be on the same page as your other ANOVA hand work. Make sure it is inserted and/or uploaded): df error = tcrit (df error) MS error = s = LSD = _____________ Mean Comparisons: Mean5 min vs. Mean10 min = | ___ __ | = ___ ___ Greater than (>) LSD value? __ ___ Significant?__ ___ Mean10 min vs. Mean15 min = |__________________| = ______ Greater…
We are interested in estimating the proportion of people that can identify Nebraska but not Vermont. In a class of 55 students, each student was requested to select a sample of 6 people, show each person a map of the US and ask the person to identify the states of Vermont and Nebraska. The following numbers are the counts that each student got, that is, each number is the count of people in the student sample of 6, that could identify Nebraska but not Vermont.3344010110020030002020001100002010000001000200000001010Note: You can cut and past these numbers into an excel spreadsheet to help you calculate the mean and the standard deviation and compute the confidence interval. If you have trouble pasting them, paste them to a text file first and then copy from there.When we collect all the students' data, we have a sample size of 6x55=330.Of the sample of 330 people, what proportion were able to locate Nebraska but not Vermont? (round answer to 3 decimals) Find a 95% confidence interval for…
Psychologists at Disney World measured factors that affect the scariness of the soundtrack for their Haunted House ride. In particular, they were interested in the loudness of the screams (soft versus loud) and the length of the screams (short versus long). They used a 2 × 2 factorial design to test how these factors combined. They collected data from 10 different riders in each of the four conditions. Each rider rated the scariness of the ride on a nine-point scale. short screams long screams soft screams T=38, n = 10, SS = 13.6 T=64, n = 10, SS = 22.4 loud screams T=52, n=10, SS = 29.6 T=50, n=10, SS = 16.0 For these data: G = 204, N = 40, X2 = 1156. 1. Sketch a dataplot of the mean rating in each condition. 2. Calculate SS total, the total sum of squares 3. Calculate SSwithin, the within-treatments sum of squares. 4. Calculate SSbetween, the between-treatments sum of squares. 5. Calculate SSA the sum of squares for Factor A (length of scream). 6. Calculate SSB, the sum of squares…
To determine the amount of sugar in a typical serving of breakfast cereal, a student randomly selected 60 boxes of different types of cereal from the shelves of a large grocery store. The student noticed that the side panels of some of the cereal boxes showed sugar content based on one-cup servings, while others showed sugar content based on three- quarter-cup servings. Many of the cereal boxes with side panels that showed three-quarter-cup servings were ones that appealed to young children, and the student wondered whether there might be some difference in the sugar content of the cereals that showed different-size servings on their side panels. To investigate the question, the data were separated into two groups. One group consisted of 29 cereals that showed one-cup serving sizes; the other group consisted of 31 cereals that showed three-quarter cup serving sizes. The boxplots shown below display sugar content (in grams) per serving of the cereals for each of the two serving sizes.…
A local health department believes that a store is merchandising its cereal aisle in a way that puts sugary cereal brands at eye level for children. The store claims that it is not considering sugar content and is stocking the shelves based on other factors. An inspector visited the store and recorded the sugar content per serving listed on the boxes (sugar content for each box is listed under the shelf where that box of cereal is located). Shelf 1 Shelf 2 Shelf 3 Shelf 4 7 13 6 10 8. 5 14 7 8 11 11 10 11 3 a) What are the treatment groups, and how many experimental units are there per treatment? b) If instead of using the content listed on the box, the inspector sampled from multiple boxes of each brand of cereal and tested them for sugar content. How many experimental units were there be if there were 10 boxes per brand on the shelf? Explain your answer. [hint: all the boxes for each brand will be in one place] c) State the null hypothesis and create an ANOVA table based on sugar…
A manufacturing plant makes computer chips 24 hours a day. Employees work one of three, 8 hour shifts during the morning (2am-10am), day (10am-6pm), and night (6pm-2am). Below are data on the number of defective chips on a randomly chosen 24 hour period. Shift Morning Day Night Number of Defective Chips 23 26 47 Total Chips Manufactured 330 330 330 The plant manager thinks there might be more defective computer chips manufactured during the night shift compared to the day shift. Give appropriate statistical evidence to test the managers' claim.
Suppose that Mary, Gary, and Larry have been asked to randomly sample 100 patients' visit records from a file of 2000 patient records and record the amount of time the attending physician spent with each patient. Gary suggests the time of year during which the patient was seen may be a confounding variable and strongly advises dividing the year into quarters (Jan - Mar, Apr-Jun, Jul-Sep, Oct- Dec) and randomly selecting 25 patient records from each quarter. Which of the following best describes Gary's sampling plan? (A) A simple random sample (B) A systematic random sample (C) A stratified random sample (D) A cluster sample (E) A convenience sample
Name each experimental design (a through e). Describe each factor - how many levels and the type of factor. Note: Gn denotes a group of subjects, and An, Bn, or Cn is a level of factor A, B, or C. [key words: ANOVA data, nested, factors, factorial design, between subject, within subject, etc.]

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