In a random sample of 200 women, age 21 or older, 140 are married. The graph shown represents the simulation of 200 women, 400 times, assuming that 140 of the women are married.Frequency8060200126128130133 134 136 139 140 142The Number of Married Women146 0|©2022A126BCD128E130132Which THREE statements can be used to describe the model?134136138140142The Number of Married Women144Illuminate Education TM, Inc.14614895% of the number of married women fall between 136 and 144.95% of the number of married women fall between 132 and 148.150152154A study claims "50% of women 21 and older are married." The results of this simulation contradict this claim.A study claims "66% of women 21 and older are married." The results of this simulation contradict this claim.A study claims "80% of women 21 and older are married." The results of this simulation contradict this claim.NO

Given that x=140 and n=200 and the sample proportion is p^=xn. The sample standard deviation is…

Answered: Which THREE statements can be used to…

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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Determine whether the study depicts an observational study or an experiment. A scientist was studying the effects of a new fertilizer on crop yield. She randomly assigned half of the plots on a farm to group one and the remaining plots to group two. On the plots in group one, the new fertilizer was used for a year. On the plots in group two, the old fertilizer was used. At the end of the year the average crop yield for the plots in group one was compared with the average crop yield for the plots in group two.
18Help me answer the question
An economist wants to determine whether there is a linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. The data are shown in the table below. c. Compute and interpret the correlation coefficient. d. Compute and interpret the coefficient of determination. e. Test for the significance of the linear relationship. Use a 0.05 level of significance. State your conclusion. Hint: Your conclusion is either of the following. • There is a significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. • There is no significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. GDP 1.6 3.6 4.9 1.1 0.9 2.9 2.7 2.3 1.6 1.5 (trillion dollars) Carbon Dioxide Emissions 428.2 828.8 1214.2 444.6 264 415.3 571.8 454.9 358.7 573.5 (millions of metric tons)
Section 10.2 Question #12 Find the regression equation, letting the diameter be the predictor (x) variable. Find the best predicted circumference of a marblewith a diameter of 1.2 cm. How does the result compare to the actual circumference of 3.8 cm? Use a significance level of 0.05. Baseball Basketball Golf Soccer Tennis Ping-Pong Volleyball Diameter 7.5 24.3 4.2 21.7 6.9 4.1 20.7 Circumference 23.6 76.3 13.2 68.2 21.7 12.9 65.0 View the critical values of the Pearson correlation coefficient r. Critical values of the pearson correlation coefficient r n α=0.05 α=0.01 NOTE: To test H0: ρ=0 against H1: ρ≠0, reject H0 if the absolute value of r is greater than the critical value in the table. 4 0.950 0.990 5 0.878 0.959 6 0.811 0.917 7 0.754 0.875 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576…
For each of the following variables, indicate whether they are categorical or numerical. Also, write down what type of graph can be drawn for each. a) Position of a university staff members. b) Weight of participants. C Air temperature on the Celsius scale D) The daily number of code lines written by a programmer
A psychologist would like to examine the effects of a new drug on the activity level of animals. Three samples of rats are selected with n=5 in each sample. One group gets no drug, one group gets s small dose, and the third group gets a large dose. The psychologist records the activity level for each animal. The data from this experiment are presented below. No drug Small dose Large dose 5, 3 , 1 , 1 , 5 5, 5, 9, 6, 5 10, 12, 9, 6, 8 =3, SS=16 =6, SS=12 =9, SS=20 Do these data indicate any significant differences among the three groups? Test with α=0.05. Compute the effect size and interpret the result.
Consider the following passage: I ran a regression, with many variables to predict the result of another variable which was the murder rate. One can see that lots of things, can cause the murder rate to increase or decrease. I tried to account for all the important factors, and those factors are the SAT scores, unemployment rate, and international migration per 1,000. The SAT score is, average combined total score participants did on the SAT exam. The unemployment rate is, "a measure of the prevalence of unemployment and it is calculated as a percentage by dividing the number of unemployed individuals by all individuals currently in the labor force." (Wikipedia) International migration per 1,000 is, the number of people who come into a state from other countries per 1,000 people who live in the state. After I run the regression I will look at the t scores and p values and I should hopefully conclude that international migration does not cause crime. Which writing mistakes, if any, did…
Section 10.2 Question #11 The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $11million. Is the result close to the actual number of viewers, 3.3 million? Use a significance level of 0.05. Salary (millions of $) 108 15 2 15 3 8 4 14 Viewers (millions) 9.1 9.3 10.9 1.3 4.8 4.8 3.2 1.8 View the critical values of the Pearson correlation coefficient r. Critical values of the pearson correlation coefficient r n α=0.05 α=0.01 NOTE: To test H0: ρ=0 against H1: ρ≠0,reject H0if the absolute value of r is greater than the critical value in the table. 4 0.950 0.990 5 0.878 0.959 6 0.811 0.917 7 0.754 0.875 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735…
A random sample of 136 adults were asked to report the number of hours per week the spent on a computer and their number of years of education. The linear model equation below describes the relationship between the mean computers hours and years of education. computers == 9.12 ++ 0.8 ×× education Based on this linear model, which of the following statements is correct? a) An adult who has no years of education is expected to spend 9.12 hours per week on a computer. b) An adult who has 1 more year of education than another is expected to spend 9.12 more hours per week on a computer. c) An adult who spends 1 more hour per week on a computer than another is expected to have had 9.12 more years of education. d) An adult who spend zero hours per week on a computer is expected to have 9.12 years of education.
Scenario: Album Sales: A study was done to see whether getting radio airtime and spending money on advertisements accurately predicts the number of album copies sold. A random sample of 200 artists’ albums were tracked on the number of times their songs play on the central radio station, how much money (in thousands) they spent on advertisements, as well as the number (in thousands) of album copies were sold. A record company wanted to determine if there was a positive relationship between album sales and the other two variables (money spent on advertisements and number of albums sold) What is the Null and alternative hypotheses (based on context of study) in symbols and words:
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
need help in d and e

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