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- A)Test the claim, at the a = 0.10 level of significance, that a linear relation exists between the two variables, for the data below, given that y-1.885x +0.758. -5 |-3| 4 11 6 y Step 1) State the null and alternative hypotheses. Step 2) Determine the critical value for the level of significance, a. Step 3) Find the test statistic or P-value. Step 4) Will the researcher reject the null hypothesis or do not the null hypothesis? Step 5) Write the conclusion. B) The regression line for the given data is v = -1.885x + 0.758. Determine the residual of a data point for which x = 2 and y = -4. SAMSUNG DII 96 &Data are collected in an experiment designed to in- vestigate the impact of different positions of the mother during ultrasound on fetal heart rate. Fetal heart rate is measured by ultrasound in beats per minute. The study includes 20 women who are as- signed to one position and have the fetal heart rate measured in that position. Each woman is between 28 weeks and 32 weeks gestation. The data are shown in Table 7–7. Is there a significant difference in mean fetal heart rates by position? Run the test at a 5% level of significance. back side sitting standing 140 141 144 147 144 143 145 145 146 145 147 148 141 144 148 149 139 136 144 145Which scatter plot includes the given data points?
- 5. Which of the following is the assumption that the best way to describe the pattern of data is using a straight line? homoscedasticity normality linearity restriction of range3. What percentage of College students have made at least one online purchase in the last three months? To answer this question, a market researcher surveyed 200 college students. Of those surveyed, 76 said that they had made at least one online purchase (a.) What is the parameter of interest in this study? (b.) Calculate the corresponding point estimate of the population proportQ3: From the below Table, answer the following questions: NO Age Gender Salary 1001 20 1002 1003 22 30 1004 25 1005 34 1006 35 1007 38 1008 35 1009 30 M F F M F M F M 280 300 450 310 320 340 350 500 450 1)Trimmed mean 5% of age variable= 2) Interquartile Range of salary variable = 3) Variance of age variable = 4) Mean of salary variable = 5) represent the Gender variable by pie chart, showing the frequencies on it.
- This exercise requires the use of a statistical software package. The cotton aphid poses a threat to cotton crops. The accompanying data on y = Infestation rate (aphids/100 leaves) x1 = Mean temperature (°C) x2 = Mean relative humidity appeared in an article on the subject. y x1 x2 y x1 x2 62 21.0 57.0 76 24.8 48.0 86 28.3 41.5 94 26.0 56.0 99 27.5 58.0 99 27.1 31.0 105 26.8 36.5 119 29.0 41.0 101 28.3 40.0 75 34.0 25.0 64 30.5 34.0 44 28.3 13.0 28 30.8 37.0 18 31.0 19.0 15 33.6 20.0 22 31.8 17.0 31 31.3 21.0 24 33.5 18.5 68 33.0 24.5 41 34.5 16.0 5 34.3 6.0 22 34.3 26.0 19 33.0 21.0 24 26.5 26.0 43 32.0 28.0 55 27.3 24.5 59 27.8 39.0 60 25.8 29.0 81 25.0 41.0 88 18.5 53.5 76 26.0 51.0 103 19.0 48.0 109 18.0 70.0 96 16.3 79.5 Find the estimated regression equation of the multiple regression model y = ? + ?1x1 + ?2x2 + e. (Round your numerical values to two decimal places.) = Assess the utility of the…Q1. A psychologist conducted a study on the relationship between introversion and shyness. The values are results for scales of introversion and shyness. High positive scores on each scale indicate high introversion or shyness; and high negative scores indicate low introversion or shyness. Data collected from 10 people as follows: Introversion 4 -7 -1 0 6 7 -4 -9 -5 8 Shyness 11 -7 -1 -3 0 7 -1 -8 -1 5 a) Compute the correlation coefficient relating introversion and shyness scores. b) Find the regression equation which predicts introversion from shyness. c) What introversion score would you predict from a shyness score of 7?This dataset of size n - 51 is for the 50 states and the District of Columbia in the United States. The variables are - year 2002 birth rate per 1000 females 15 to 17 years old and z- poverty rate (the percent of the state's population living in households with in- comes below the federally defined poverty level) i- 13.1 - 22.3 R- 51, Su - E(-2) - 914.7 S, - E( -2)( - 6) - 1, 256.2 Su - E(m - M) - 3, 249 SSE - E(w - - 1, 509.6 1. Find A. A and r. 2. Write the fitted linear regression model for ý, in terms of z, A, and A- For A and , use the values you obtained in problem 1. 3. Interpret the slope of the least squares line based on the context. 4. Find SST, SE and SSR. 5. Find R* and . 6. Complete a chart for ANOVA df MS pvalue Source Regression Error Total 7. Complete a chart for Parameter Estimates. t-value pvalue Parameter Intercept Slope Estimate S.e. 8. What is the residual e, for the observation (.) - (20.1,31.5)? 9. What is the conclusion for the test Ha : -0 vs Ho : +0 with a -…
- 13.2.34. 0 There is some indication that as countries' levels of literacy increases, authoritarian tendencies decline among the population. The following data show literacy (measured in number of literate people per 10 people) and authoritarian scores on a standard authoritarinaism- measuring scale from 8 countries. The data are: Xiiteracy : 9.2, 7.5, 8.8, 6.5, 4.3, 5.9, 9.7, 8.5 XAuth: 2.1, 3.4, 2.5, 7.3, 8.9, 5.7, 1.3, 2.5 Is there a reliable relationship between the two variables? If yes, what would the predicted authoritarian score of a country where only quarter of the country is literate? What about for a country where the literacy rate is %100? Use alpha = .05.6.3 7) A college professor was becoming annoyed by how many of his students were absent during his 8:00 a.m. section of Philosophy 103. He decided to analyze whether these absences were impacting student scores. He assigned his TA the task of keeping track of attendance. At the end of the semester he compared each student's grade on the final exam (100 points possible) with the number of times he or she had been absent. His findings are displayed in the graph to the right. a) Identify the explanatory and response variables. Absences & Final Exam Scores b) Describe the relationship between these two variables. (Form, Direction, Strength, Outliers) 0 Number of Absences (87 total days) c) Jeremy was absent 25 times. What would you predict his score on the final exam to be? d) Lucy often overslept and missed 43 class sessions. What would you predict for her score on the final? Grade on Final Exam 88228892290 100 20 91.704-1.654x R²=0.8732