**Analysis of Fruit Fly Lifespan Using Two-Factor ANOVA**The study measured the life span (days) of three genotypes of fruit flies for both males and females. A two-factor ANOVA was performed to test for significant differences in life span among genotypes (factor A), between sexes (factor B), and to assess for a genotype-sex interaction. A 5% level of significance was used for each test.### Two-Factor ANOVA Table:| Source | SS | DF | MS | F ||--------------|--------|----|-----|-----|| Genotype | 454.01 | 3 | | || Sex | 73.30 | 2 | | || Interaction | 670.20 | 6 | | || Error | 1000.20| 36 | | || **Total** | 2197.71| 47 | | |**Definitions:**- **SS (Sum of Squares):** A measure of the total variability.- **DF (Degrees of Freedom):** The number of independent values or quantities which can be assigned to a statistical distribution.- **MS (Mean Square):** The average of the squared deviations (SS/DF).- **F:** The F-ratio, a statistic for comparing model fits.**Conclusion:**The question asks you to conclude whether there is a significant effect due to the three genotypes on the life span of fruit flies. You do not need to fill out the entire table to answer.**Conclusion Options:**1. There is no effect due to the three genotypes.2. There is a significant effect due to the three genotypes.3. The genotypes have a significant effect on the results of the Two-factor ANOVA.**Hint:**The conclusion should focus on the effect of the three genotypes on the life span of fruit flies specifically, considering the given information and the 5% significance level.

Name: **Analysis of Fruit Fly Lifespan Using Two-Factor ANOVA**The study me
Uploaded: 2024-03-20T07:06:27.000Z
Channel: Bartleby
Description: **Analysis of Fruit Fly Lifespan Using Two-Factor ANOVA**The study measured the life span (days) of three genotypes of fruit flies for both males and females. A two-factor ANOVA was performed to test for significant differences in life span among ge

The ANOVA table with some missing are given in the data.

Math

Statistics

The life span (days) of three genotypes of fruit flies was measured for both males and females. Some calculations are presented below to test for significant differences in life span among genotypes (factor A), between sexes (factor B), and test for a genotype-sex interaction. Use a 5% level of significance for each test. Two-Factor ANOVA Source SS DF MS F Genotype 454.01 3 Sex 73.30 Interaction 670.20 6. Error 1000.20 36 Total 2197.71 47 What is your conclusion regarding the effects of three genotypes on the life span of fruit flies? Hint* this question is asking you to choose a conclusion for a single factor only. You do not have to fill out the entire table. There is no effect due to the three genotypes. There is a significant effect due to the three genotypes. The genotypes have a significant effect on the results of the Two-factor ANOVA.

The life span (days) of three genotypes of fruit flies was measured for both males and females. Some calculations are presented below to test for significant differences in life span among genotypes (factor A), between sexes (factor B), and test for a genotype-sex interaction. Use a 5% level of significance for each test. Two-Factor ANOVA Source SS DF MS F Genotype 454.01 3 Sex 73.30 Interaction 670.20 6. Error 1000.20 36 Total 2197.71 47 What is your conclusion regarding the effects of three genotypes on the life span of fruit flies? Hint* this question is asking you to choose a conclusion for a single factor only. You do not have to fill out the entire table. There is no effect due to the three genotypes. There is a significant effect due to the three genotypes. The genotypes have a significant effect on the results of the Two-factor ANOVA.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

Several methods of estimating the number of seeds in soil samples have been developed by ecologists. An article gave the accompanying data on the number of seeds detected by the direct method and by the stratified method for 27 soil specimens. Specimen Direct Stratified 1 21 7 2 34 38 3 0 7 4 60 58 5 20 54 6 61 61 7 40 27 8 7 7 9 14 7 10 94 100 11 1 0 12 67 58 13 78 67 14 21 54 Specimen Direct Stratified 15 34 27 16 0 0 17 38 38 18 18 14 19 94 94 20 1 14 21 40 47 22 21 21 23 0 0 24 7 14 25 14 40 26 18 14 27 40 78 Do the data provide sufficient evidence to conclude that the mean number of seeds detected differs for the two methods? Test the relevant hypotheses using ? = 0.05. (Use ?direct − ?stratified.) Find the test statistic. (Round your answer to two decimal places.) t = Find the df. (Round your answer down to the nearest whole number.) df = Use technology to find the P-value. (Round your answer to four…
Define a suitable population, variable/s, and the parameter of interest for the following study: A market researcher wishes to determine the market share of the four leading brands of cereal among children in Davao City who are 12 years old or younger What is the Population? Variable/s? K Parameter of Interest?
A researcher would like to know which factors are most important to people who are buying a new car. A sample of n=200 customers between the ages of 20 and 29 are asked to identify the most important factor in the decision process: Performance, Reliability, or Style. The researcher would like to know whether there is a difference between the factors identified by women compared to those identified by men. The data are as follows: Observed Frequencies of Most Important Factors According to Gender: Performance Reliability Style Total Male 21 33 26 80 Female 19 67 34 120 Total 40 100 60 Compute the expected frequencies (fill in chart). Expected Frequencies: Performance Reliability Style Male Female
The life span (days) of three genotypes of fruit flies was measured for both males and females. Some calculations are presented below to test for significant differences in life span among genotypes (factor A). between sexes (factor B), and test for a genotype-sex interaction. Use a 5% level of significance for each test. Two-Factor ANOVA Source DF MS Genotype 454.01 3 Sex 73.30 Interaction 670.20 6. Error 1000.20 36 Total 2197.71 47 What is your conclusion regarding the effects of the sexes on the life span of fruit flies? Hint" this question is asking you to choose a conclusion for a single factor anly. You do not hove to Mout the entire table. O The sexes have a significant effect on the results of the Two-factor ANOVA O There is a signifhcant etfect due to the sex of fruit fies O There is no effect due to the sex of fruit flies.
Several methods of estimating the number of seeds in soil samples have been developed by ecologists. An article gave the accompanying data on the number of seeds detected by the direct method and by the stratified method for 27 soil specimens. Specimen Direct Stratified 1 21 6 2 32 38 3 0 6 4 60 58 5 20 52 6 61 61 7 40 26 8 6 6 9 12 6 10 92 100 11 1 0 12 66 58 13 78 66 14 21 52 Specimen Direct Stratified 15 32 26 16 0 0 17 38 38 18 18 12 19 92 92 20 1 12 21 40 46 22 21 21 23 0 0 24 6 12 25 12 40 26 18 12 27 40 78 Do the data provide sufficient evidence to conclude that the mean number of seeds detected differs for the two methods? Test the relevant hypotheses using ? = 0.05. (Use ?direct − ?stratified.) Find the test statistic. (Round your answer to two decimal places.) t = Find the df. (Round your answer down to the nearest whole number.) df = Use technology to find the P-value. (Round your answer to four…
Create an Excel Spreadsheet for a beer rating study Evaluate the impact of caffeine on crankiness Write the APA formatted results for this analysis, including R2 for the results and post hoc analyses if needed Participant ID. Caffeine Level Crankiness Score 1 0 MG 40 2 0 MG 42 3 0 MG 30 1 50 MG 30 2 50 MG. 45 3 50 MG 38 1 100 MG 53 2 100 MG 65 3 100 MG 64
A recent poll revealed the political affiliations of 205 Americans, along with the region of the country in which they reside. Political Affiliation Democrat Independent Republican Northeast 14 26 12 Region Southeast 13 23 17 West 34 37 29 If you wish, you may download the data in your preferred format. CrunchIt! CSV Excel JMP Mac Text Minitab PC Text R SPSS TI Calc To test whether region of residence and political affiliation were related, one of the pollsters computed a chi-squard statistic, x = 3.4318, with four degrees of freedom and set an alpha (a) level of 0.05. Determine the P-value of the chi-square statistic in this test for independence and report it to at least three decimal places. You will need to use some kind of software (statistical package or calculator that does statistical computations) to get the P-value that precisely. P%3D
Including the population size n for each category of individuals in the study will allow researchers to compare the sample sizes and determine if there is a significant difference in the power between two groups that may be influencing the effect size of any of the observed results from a study. Group of answer choices True False
The National Football League (NFL) records a variety of performance data for individuals and teams. To investigate the importance of passing on the percentage of games won by a team, the following data show the average number of passing yards per attempt (Yds/Att) and the percentage of games won (WinPct) for a random sample of 10 NFL teams for the 2011 season (NFL website). Team Yds/Att WinPct 5.7 26 Arizona Cardinals Atlanta Falcons Carolina Panthers 7.6 67 7.3 52 6.9 51 Chicago Bears Dallas Cowboys 5.1 17 8.6 82 New England Patriots Philadelphia Eagles Seattle Seahawks 5.3 21 6.6 41 St. Louis Rams 6.5 41 Tampa Bay Buccaneers. 6.1 38 a. Choose the correct a scatter diagram with the number of passing yards per attempt on the horizontal axis and the percentage of games won on the vertical axis. B. A. WinPct WinPct 80 DD J F1 70- 60- 50+ -40- 30 20- F2 80 F3 000 000 F4 F5 80- -70 60- 50- 40- 30- 20- S F6 ● - F7 DII F8 F9 F10 () F11 <))) F12 A
toto In physiology, an objective measure of aerobic fitness is how efficiently the body can absorb and use oxygen (oxygen consumption). A physiologist, Dr. Castillejo, conducted a research wherein subjects participated in a predetermined exercise run of 1.5 miles. Measurements of oxygen consumption as well as several other variables such as age, gender, runtime, resting and maximum pulse rates, and weight were recorded from 50 randomly selected gym members. Dr. Castillejo is interested in determining whether any of these other variables can help predict oxygen consumption. She believes that a possible link between these factors will help her determine how to improve the health of her gym members. Help Dr. Castillejo in developing a proposal for the improvement of her gym members' health condition. The variables are described below. gender- either male or female runtime-time to run 1.5 miles (in min) age - age of the gym member in years weight-weight of the gym member (in kg) oxygen…
his question refers to excavations at a national monument. One question the archaeologists asked was: Is raw material used by prehistoric Indians for stone tool manufacture independent of the archaeological excavation site? Two different excavation sites gave the information in the following table. Use a chi-square test with 5% level of significance to test the claim that raw material used for construction of stone tools and excavation site are independent. Excavation Site Material Site A Site B Row Total Basalt 756 559 1315 Obsidian 92 103 195 Pedernal chert 514 521 1035 Other 88 91 179 Column Total 1450 1274 2724 (a) What is the level of significance? (b) Find the value of the chi-square statistic for the sample. (Round the expected frequencies to at least three decimal places. Round the test statistic to three decimal places.)
A team of epidemiologists at the Mayo Clinic wanted to find whether there is an association between obesity and cardiovascular disease (CVD). They conducted a prospective cohort study following obese and non-obese individuals who were free of CVD at the beginning of study for five years. The investigators were also interested in assessing age as a potential confounder, effect modifier, or both. Use the data below to answer the accompanying questions. CVD No CVD Total Obese 10 90 100 Not Obese 35 465 500 Total 45 555 600 CVD No CVD Total Obese 36 164 200 Not Obese 25 175 200 Total 61 339 400 1. Compute the appropriate measure of association for those who were less than age 50. 2. Compute the appropriate measure of association for those who were older or equal to age 50. 3. Compute the crude measure of association? 4. List three attributes that age must satisfy before it could…