À researcher wishes to test the idea that shoe size and mathematical ability are correlated;, that is, people with larger feet have higher mathematical skills. To test this he conducts a study of an entire town of 2000 persons measuring their shoe size and administering a math test. He finds that there is a significant correlation between shoe size and math skills with people with larger feet having higher math skills. (a) What might an important problem with this approach? (b) The researcher decides to use data only for adults ages 21 to 60 to compute a correlation coefficient. What value of r should he expect?
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- For a random sample of households in the US, we record annual household income, whether the location is east or west of the Mississippi River, and number of children. We are interested in determining whether or not there is a linear relationship between household income and number of children. Part 1 (a) State the null and alternative hypotheses. Ho: II vs Ha: 44₁ :: p ₂ ^ P₁ p II :: P₁ A P₂ : 0 pA graduate student is interested in how viewing different types of scenes affects working memory. For his study, he selects a random sample of 36 adults. The subjects complete a series of working memory tests before and after walking in an urban setting. Before the walk, the mean score on the test of working memory was 9.1. After the walk, the mean score was 1.4 higher. The graduate student has no presupposed assumptions about how viewing different types of scenes affects working memory, so he formulates the null and alternative hypotheses as: H00 : μDD = 0 H11 : μDD ≠ 0 Assume that the data satisfy all of the required assumptions for a repeated-measures t test. The graduate student calculates the following statistics for his hypothesis test: Mean difference (MDD) 1.4 Estimated population standard deviation of the differences (s) 1.6 Estimated standard error of the mean differences (sMDMD) 0.2667 Degrees of freedom (df) 35 The t statistic 5.25 The critical values of t…ab! ourses The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technology was also given a foot length of 13.6 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 13.6 cm, what is the single value that is the best predicted height for that person? "se Hom E Click the icon to view the technology output. abus The single value that is the best predicted height is cm. endar (Round to the nearest whole number as needed.) entation ktbook a-F on unouncem ssignment: cudy Plan radebook Hydrogen Report.pdf Enter your answer in the answer box. Screen Shot 20-11...9.53 P 5,981 10 tv MacBook Pro (5
- Kris works for the MESA Air Pollution Study at UW, and studies the correlation be- tween air pollution and the disease atherosclerosis. Nationally, 40% of adults suffer from atherosclerosis. Kris suspects that the proportion of people with atherosclerosis in high- pollution areas is higher. In a random sample of 600 residents of high-pollution areas, he finds that 270 (45%) subjects have atherosclerosis. At the 1% level (α = .01), is this good evidence that people in high-pollution areas are more likely to have atherosclerosis? (a) Which of the following is the Ha ? (research claim or alternate) A. Ha : p ≥ 0.40 B. Ha : pb ≥ 0.40 C. Ha : p > 0.40 D. Ha : p > b 0.40 E. Ha : p > b 0.45 F. Ha : p > 0.45 G. Ha : pb ≥ 0.45 H. Ha : p ≥ 0.45 I. None of these Hint: First read the problem and using my notes (or Hawkes) for 9.1, set up H0 and Ha . Then pick the right Ha from the above list. Dont try to guess the answer from the above list. (b) Which of the…Investigation 3.2: Valence Differences Between R&B and Rap Genres (Paired)A music fan claims that R&B songs tend to have a more positive tone on average than do Rapsongs. The individual collected two independent random samples from the population of SpotifySongs. Fifteen R&B songs and another fifteen Rap songs were collected and their Valence wasrecorded. The music fan believed that pairing the song by their Danceability may provideadditional information. Danceability describes how suitable a track is for dancing based on acombination of musical elements including tempo, rhythm stability, beat strength, and overallregularity. A value of 0.0 is least danceable and 1 is most danceable. Thus, the individual pairedthe R&B song with the lowest danceability with the Rap song with the lowest danceability,followed by the second and second, third and third. She continued this process until the R&Bsong with the highest danceability was paired with the Rap song with the…There are many ways to measure the reading ability of children. Research designed toimprove reading performance is dependent on good measures of the outcome. Onefrequently used test is the DRP, or Degree of Reading Power. A researcher suspects that themean score µ of all third- graders in Henrico County Schools is different from the nationalmean, which is 32. To test her suspicion, she administers the DRP to an SRS of 44 HenricoCounty third-grade students. The distribution of scores is summarized in the Minitab outputbelow: MEAN STDEV SEMEAN MIN Q1 MEDIAN Q3MAXDRP 35.09 11.19 1.69 14.00 26.00 35.00 44.0054.00 Construct a 90% confidence interval to estimate the mean DRP score in Henrico CountySchools.
- An Economics instructor assigns a class to investigate factors associated with the gross domestic product (GDP) of nations. Each student examines a different factor (such as life expectancy, literacy rate, etc.) for a few countries and reports to the class. Apparently, some of the classmates do not understand Statistics very well because several of their conclusions are incorrect. Explain the mistakes in comments a and b below. a) Explain the mistake in the statement "There was a very strong correlation of 1.22 between Life Expectancy and GDP" Choose the correct answer below O A. A correlation cannot be greater than 1. O B. A correlation that is greater than 1 implies that the variables are not quantitative, so the correlation cannot be interpreted. OC. A correlation that is close to 1 implies a very weak correlation. The correlation must be close to 10 for it to be interpreted as a very strong correlation. O D. A correlation that is greater than 1 implies a weak correlation, not a…In a study examining the relation of math ability to the belief that math ability was innate, the belief was considered the predictor variable. The researcher hopes to find a correlation between the participants’ math ability and their belief that math ability is innate. The scores for the three participants are shown below. The group that believed that math is NOT innate scored 66, 70, 50. The group that believed that math IS innate scored 7, 4,10. Calculate, by hand, the correlation between these two variables. Is it positive or negative and is it a strong correlation?The correlation between mean 2015 Mathematics SAT scores and mean 2015 Writing SAT scores for all 50 states and the District of Columbia is 0.983.0.983. Would one expect the correlation between the mean state SAT scores for these two tests to be lower, about the same, or higher than the correlation between the scores of individuals on these two tests?
- The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technologgy was also given a foot length of 10.8 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 10.8 cm, what is the single value that is the best predicted height for that person? H Click the icon to view the technology output. The single value that is the best predicted height is cm. Technology Output (Round to the nearest whole number as needed.) The regression equation is Height - 67.5 +5.15 Foot Length Predictor Coef SE Coef Constant 67.52 11.07 6.10 0.000 Foot Length 5.1508 0.4817 10.69 0.000 S-5.50271 R-Sq = 73.18 R-Sq (adj) = 72.44 Predicted Values for New Observations New Obs Fit SE Fit 95 CI 954 PI 123.149 1.605 (119.732, 126.566) (111.996, 134.302) Values of Predictors for New…. Dr. Hafen is doing research on the effects of study time (how many minutes students study) on test performance (their score on an exam). He hypothesizes that the amount of study time will impact an individual’s performance on the exam. Then Dr. Hafen collects data on 100 students. He collects data on their ‘study time’ and their ‘exam performance’, then runs a Pearson correlation. In your own words, please describe what Dr. Hafen’s null hypothesis would be and what Dr. Hafen’s alternative hypothesis would be. If Dr. Hafen makes a Type I error, what would that mean in the context of this study? If he makes a Type II error, what would that mean in the context of this study?The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technology was also given a foot length of 17.8 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 17.8 cm, what is the single value that is the best predicted height for that person? Click the icon to view the technology output. The single value that is the best predicted height is (Round to the nearest whole number as needed.) cm. Technology Output The regression equation is Height = 53.3+4.25 Foot Length Predictor Constant Coef SE Coef 53.28 11.44 Foot Length 4.2537 0.4699 S = 5.50739 R-Sq=72.3% R-Sq (adj) = 71.6% T 4.66 9.05 Predicted Values for New Observations New Obs 1 Fit SE Fit 128.996 1.733 (124.309, 133.683) 95% CI Foot New Obs Length 1 17.8 0.000 0.000 Values of Predictors for New…