For each of the following hypothetical studies, identify the primary caution eac

Question

For each of the following hypothetical studies, identify the primary caution each researcher should have when drawing conclusions about the relationship he or she found. Sarah wants to determine the relationship between height and weight for high school students in the United States. She collects data on height, in inches, and weight, in pounds, for 75 randomly selected high school students in each state. She averages the values by state and performs a linear regression on the 50 state-level values. She finds a high positive linear correlation between height and weight. Otis set up a study along a temperature gradient where the mean maximum July temperature ranges from 19 to 30 °C. He tracked the number of eggs laid by 105 breeding pairs of barn owls along this gradient over one year, and found a strong positive linear association between the number of eggs laid and mean maximum July temperature. He used the linear regression to predict the number of eggs barn owls lay each year in an area with a mean maximum July temperature of 40 °C. Lucy used linear regression to determine how household annual income influenced household credit card debt for a sample of 225 households. The household income level for most of her samples ranged from $37,000 to $82,000. However, the income level for one household was $26,000. The slope of the regression line changed markedly when Luey removed this data point from her analysis. George measured the tail length, in em, of 106 spider monkeys living in captivity, and the consumption had a strong positive linear association with tail length. George concluded the amount of food each spider monkey consumed per day, in grams. He found that food amount of food spider monkeys eat is determined by their tail length. Answer Bank influential observationrking variable extrapolation ecological correlation

Explanation / Answer

Part I

Primary caution: the sample must be of same age group in all the states

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Part II:

The range of regression data is from 19 to 30 degree

The prediction must be done within this range of temperature only

Linear regression does not help for the ranges beyond the data employed to create the regression model

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Part III

It is important to analyze the outliers and make sure that the data collected covers the population completely

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Part IV:

The sample does not consists of all the free monkeys. It consists of the monkeys in the captivity. Hence the results cannot be actually generalized and effect of confounding variables must be considered in this scenario

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