Concept explainers
Each of the following studies examines the relationship between sugar consumption and activity level for preschool children. Identify which is
Study 1: A researcher obtains a sample of 100 pre-school children. Each child’s parents are interviewed to determine the child’s typical diet, and the child is assigned a score describing the amount of sugar consumed daily. Also, the child’s activity level is obtained from direct observation on the playground. The results show that higher sugar consumption tends to be associated with a higher level of activity.
Study 2: A researcher obtains a sample of 100 pre-school children. The children are randomly assigned to two groups. On arriving at school each morning, one group is given a high-sugar breakfast, and the other group is given a breakfast relatively low in sugar. After 1 week, each child’s activity level is measured by direct observation on the playground. On average, the children in the high-sugar breakfast group had a higher level of activity than the children in the low-sugar group.
Study 3: A researcher obtains a sample of 100 pre-school children. Based on interviews with the parents, the children are divided into two groups corresponding to high-sugar and low-sugar diets. The children are then observed on the playground Lo obtain an activity-level score for each child. On average, the children in the high-sugar group had higher activity scores than the children in the low-sugar group.
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Chapter 12 Solutions
Research Methods for the Behavioral Sciences
- Urban Travel Times Population of cities and driving times are related, as shown in the accompanying table, which shows the 1960 population N, in thousands, for several cities, together with the average time T, in minutes, sent by residents driving to work. City Population N Driving time T Los Angeles 6489 16.8 Pittsburgh 1804 12.6 Washington 1808 14.3 Hutchinson 38 6.1 Nashville 347 10.8 Tallahassee 48 7.3 An analysis of these data, along with data from 17 other cities in the United States and Canada, led to a power model of average driving time as a function of population. a Construct a power model of driving time in minutes as a function of population measured in thousands b Is average driving time in Pittsburgh more or less than would be expected from its population? c If you wish to move to a smaller city to reduce your average driving time to work by 25, how much smaller should the city be?arrow_forwardResearchers interested in determining if there is a relationship between death anxiety and religiosity conducted the following study. Subjects completed a death anxiety scale (high score = high anxiety) and also completed a checklist designed to measure an individuals degree of religiosity (high score = greater religiosity) . A normally distributed, randomly selected data sample is provided below . What is the degree of relationship between the two variables? Death Anxiety Religiosity 38 4 42 3 29 11 31 5 28 9 15 6 24 14 17 9 19 10 11 15 8 19 19 17 3 10 14 14 6 18arrow_forwardA researcher was interested in knowing the relationship between asthma and mental illness among Veterans. As such, she surveyed a group of 15,000 Veterans On May 2024 to evaluate how many of them reported both mental illness as well as asthma. What type of study is it: prosepctive cohort study case-control study cross-sectional study retrospective cohort studyarrow_forward
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- An experiment was conducted to compare the alcohol content of soy sauce on two different production lines. Production was monitored eight times a day. The data are shown here. Production line 1 0.38 0.37 0.39 0.41 0.38 0.39 0.40 0.39 Production line 2 0.48 0.39 0.42 0.52 0.40 0.48 0.52 0.52 Assume both populations are normal. It is suspected that production line 1 is not producing as consistently as production line 2 in terms of alcohol content. Perform a hypothesis test to compare the population standard deviation of these two types of production lines. What is the value of the test statistic?arrow_forwardFifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? Use a significance level of α=0.05. Correlation Results Correlation coeff, r: 0.963947 Critical r: ±0.2680855 P-value (two tailed): 0.000 Determine the null and alternative hypotheses. H0: ρ is: ≠, =, <, or > ______ H1: ρ is: <, =, >, or ≠ ______ (Type integers or decimals)arrow_forwardFifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? Use a significance level of x 0.05. Correlation Results Correlation coeff, r: 0.968882 Critical r: ±0.2680855 P-value (two tailed): 0.000 ... OC. No, because the test statistic falls between the critical values. O D. Yes, because the test statistic falls between the critical values. O E. The answer cannot be determined from the given information. When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? O A. No,…arrow_forward
- Fifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? Use a significance level of α=0.05. Correlation Results Correlation coeff, r: 0.955111 Critical r: ±0.2680855 P-value (two tailed): 0.000 Determine the null and alternative hypotheses. H0: ρ less than< not equals≠ less than< greater than> equals= nothing H1: ρarrow_forwardFifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? Use a significance level of a = 0.05 Question: Determine the null and alternative hypothesesarrow_forwardFifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? Use a significance level of a = 0.05. Correlation Results Correlation coeff, r: 0.969937 Critical r: + 0.2680855 P-value (two tailed): 0.000 B. There is one critical value at r= Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? Choose the correct answer below and, if necessary, fill in the answer box within your choice. (Round to three decimal places as needed.) A. Yes, because the absolute value of the test statistic exceeds the…arrow_forward
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