**Transcript of Study Analysis:****Date:** October 30, 2023, at 11:00 AM**Topic: Analyzing the Effectiveness of Contraceptive Treatments in Wild Horse Herds****Study Overview:**Imagine conducting an analysis on data from a study involving 45 herds of wild horses. In these herds, some female horses received contraceptive treatments to prevent pregnancies. The aim of wildlife managers is to determine the effectiveness of these treatments.**Key Analysis:**In the analysis, a linear correlation of \( r = -0.56 \) was discovered. This correlation relates the proportion of females in a herd that received the contraceptive treatment (x-variable) to the number of foals born in the herd (y-variable).**Statistical Significance Testing:**One method to assess the statistical significance of a correlation coefficient is by comparing it to a critical value from Table A-6. For this analysis, utilize the Table A-6 method with a significance level \( \alpha = 0.05 \).**Objective:**Evaluate whether the correlation coefficient significantly differs from zero. This involves determining the critical value and presenting a comprehensive conclusion regarding the meaning of the correlation. The conclusion should address the effectiveness of the contraceptive treatment.**Next Steps:**- Identify the critical value from Table A-6 for the given significance level.- Compare the calculated correlation coefficient to this critical value.- Conclude whether the contraceptive treatment is effective based on the statistical analysis. This study aims to provide insights into the management of wild horse populations through the application of contraceptive methods.

The given data is as follows:Sample size, Correlation coefficient, The objective is to compare the…

Suppose you were to analyze data from a study of 45 herds of wild horses where some of the females in each herd were being treated with contraceptives to keep them from getting pregnant. The wildlife managers in the area want to find out if the contraceptive treatment is working. Suppose in your analysis, you were to find a linear correlation of r = -0.56 between the proportion of females in a herd that had received the contraceptive treatment (the x variable) and the number of foals born in that herd (the y variable). One way to test the statistical significance of a correlation coefficient is to compare it with the appropriate critical value of r in Table A-6. Use this Table A-6 method and an a = 0.05 significance level to determine whether the correlation coefficient you found in the previous puzzle is significantly different from zero. Provide the appropriate critical value ret and a complete, written-out conclusion that explains what the correlation means, including in terms of whether the contraceptive treatment is working or not.

Suppose you were to analyze data from a study of 45 herds of wild horses where some of the females in each herd were being treated with contraceptives to keep them from getting pregnant. The wildlife managers in the area want to find out if the contraceptive treatment is working. Suppose in your analysis, you were to find a linear correlation of r = -0.56 between the proportion of females in a herd that had received the contraceptive treatment (the x variable) and the number of foals born in that herd (the y variable). One way to test the statistical significance of a correlation coefficient is to compare it with the appropriate critical value of r in Table A-6. Use this Table A-6 method and an a = 0.05 significance level to determine whether the correlation coefficient you found in the previous puzzle is significantly different from zero. Provide the appropriate critical value ret and a complete, written-out conclusion that explains what the correlation means, including in terms of whether the contraceptive treatment is working or not.

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

Can you help me out by showing me an example of a weak positive correlation scatter plot? with a relistic example that shows the two variables that demonstrate this pattern?
Over the course of a year, you find a strong, positive correlation between ice cream sales and pool drownings in a medium-sized city. The mayor decides that to prevent drownings, ice cream will be banned within the city limits. However, you show the mayor that after controlling for the high temperature of each day, the correlation between ice cream sales and number of drownings drops to zero, because that relationship was actually: Group of answer choices direct. interactive. mediating. spurious.
A researcher measures GPA and height for a group of high school students. What kind of correlation is likely to be obtained for these two variables?
For each problem, select the best response. (a) In a scatterplot of the average price of a barrel of oil and the average retail price of a gallon of gasoline, you expect to see A. a positive association. B. very little association. C. a negative association. D. None of the above. (b) If the correlation between two variables is close to 0, you can conclude that a scatterplot would show A. a cloud of points with no visible pattern.B. no straight-line pattern, but there might be a strong pattern of another form. C. a strong straight-line pattern. D. None of the above. (c) You have data for many years on the average price of a barrel of oil and the average retail price of a gallon of unleaded regular gasoline. When you make a scatterplot, the explanatory variable on the x -axis A. is the price of gasoline. B. can be either oil price or gasoline price. C. is the price of oil. D. None of the above.
A random sample of college students was surveyed about how they spend their time each week. The scatterplot below displays the relationship between the number of hours each student typically works per week at a part- or full-time job and the number of hours of television each student typically watches per week. The correlation between these variables is r = –0.63, and the equation we would use to predict hours spent watching TV based on hours spent working is as follows: Predicted hours spent watching TV = 17.21 – 0.23(hours spent working) Since we are using hours spent working to help us predict hours spent watching TV, we’d call hours spent working a(n) __________________ variable and hours spent watching TV a(n) __________________ variable. The correlation coefficient, along with what we see in the scatterplot, tells us that the relationship between the variables has a direction that is _________________ and a strength that is ______________________. According to the…
You have a theory: people who have a high income (X) are generally healthier (Y). You collect some data from local nursing homes and retirement homes and find no linear correlation between income and health. Of the 4 correlation mistakes we discussed in class, which one is the most likely here? Why? A supplements company conducted a study and found a strong positive relationship between use of its supplements and health. It advertised that it found a correlation coefficient of +1.25. What is wrong with this statement?
Suppose data are collected concerning the weight of a person in pounds and the number of calories burned in 30 minutes of walking on a treadmill at 3.5 miles per hour. How would the value of the correlation coefficient, r, change if all of the weights were converted to kilograms?
A biologist was recording various temperatures (in degrees Celsius) and predicting the amount of glucose produced by a plant (in milligrams). Suppose the linear equation was the following: ?̂ = 12.7 − 0.223? d) Suppose the correlation coefficient was −0.12. How would you classify the correlation between temperature and amount of glucose?
In a study of the stability of IQ scores, a large group of individuals is tested once at age 18 and again at age 35. The following results are obtained. At age 18: average score = 100, SD = 15 At age 35: average score = 100, SD = 15 The correlation coefficient between scores at age 18 and 35 is 0.80 and the scatter plot is football shaped. What percent of the individuals with a score of 115 at age 18 score more than 100 at age 35? Fill in the blank with a number between 0 and 100 to represent the percentage. (Do not enter the % sign.) Don't worry about rounding; any correctly rounded answer will receive full credit.
Ms. Long studied her students' physics test scores and sleeping habits. She found that students who slept less tended to earn lower scores on the test. What conclusion should she make? There is no correlation between test score and amount of sleep. There is a correlation between test score and amount of sleep. There is probably also causation. This is because there is a decrease in a student's test score with a decrease in the amount of sleep. There is a correlation between test score and amount of sleep. There may or may not be causation. Further studies would have to be done to determine this.
Melinda thinks that stress might predict lower grades on a statistics final exam. She gives a sample of statistics students a questionaire and then looks for relationships between their answers and their final exam scores. Although she finds no support for her original hypothesis, she does find that the the numbers of hours that students work outside of school is related to exam performance. When she reports the results of her study, she presents them as if the relationship between number of hours worked and exam performance was her original hypothesis. This is a questionable research practice known as: a. open science b. p-hacking c. HARKing d. constraints of generality
For item 15 and 16, refer to table below Test Result in Mathematics Frequency Score (X) 85-89 80-84 75-79 70-74 65-69 60-64 3 9 67736 8 15. How many students got scores less than 74.5? O A. 24 OB. 18 O C. 10 OD. 3 Cumulative Frequency 36 33 24 18 10 3