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Ch. 1 - Introduction to Statistics
Triola - Elementary Statistics 14th Edition
Triola14th EditionElementary StatisticsISBN: 9780137366446Not the one you use?Change textbook
Chapter 1, Problem 1.1.34

In Exercises 29–36, identify what is wrong.
Storks and Babies In the years following the end of World War II, it was found that there was a strong correlation, or association, between the number of human births and the stork population. It therefore follows that storks cause babies.

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1
Understand the concept of correlation: Correlation measures the strength and direction of a linear relationship between two variables. It does not imply causation.
Identify the logical fallacy: The statement 'storks cause babies' is an example of a post hoc fallacy, where correlation is mistaken for causation.
Consider alternative explanations: There may be external factors influencing both the stork population and human births, such as environmental changes or societal factors post-World War II.
Explore the concept of confounding variables: A confounding variable is an external factor that affects both variables being studied, potentially leading to a spurious correlation.
Emphasize the importance of rigorous analysis: To establish causation, one must conduct controlled experiments or use statistical methods to rule out confounding variables and establish a causal link.

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Key Concepts

Here are the essential concepts you must grasp in order to answer the question correctly.

Correlation vs. Causation

Correlation refers to a statistical relationship between two variables, indicating that they change together. However, this does not imply that one variable causes the other. In the storks and babies example, while there may be a correlation, it is a logical fallacy to conclude that storks cause an increase in human births without further evidence.
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Spurious Correlation

A spurious correlation occurs when two variables appear to be related but are actually influenced by a third variable or are coincidental. In the case of storks and babies, other factors, such as population growth or environmental changes, could be influencing both variables, leading to a misleading association.

Confounding Variables

Confounding variables are external factors that can affect the relationship between the independent and dependent variables in a study. In the stork and baby scenario, factors like socioeconomic conditions or urbanization trends could confound the observed correlation, making it essential to control for these variables to draw valid conclusions.
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Related Practice
Textbook Question

In Exercises 29–36, identify what is wrong.

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Textbook Question

In Exercises 21–28, determine which of the four levels of measurement (nominal, ordinal, interval, ratio) best describes the given data.

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Textbook Question

In Exercises 13–20, determine whether the results appear to have statistical significance, and also determine whether the results appear to have practical significance.


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Textbook Question

In Exercises 37–44, answer the given questions, which are related to percentages.

Checking Job Applicants In a study conducted by the Society for Human Resource Management, 347 human resource professionals were surveyed. Of those surveyed, 73% said that their companies conduct criminal background checks on all job applicants.


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b. Could the result from part (a) be the actual number of survey subjects who said that their companies conduct criminal background checks on all job applicants? Why or why not?

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Textbook Question

Quantitative/Categorical Data Identify each of the following as quantitative data or categorical data


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Textbook Question

In Exercises 21–28, determine whether the study is an experiment or an observational study, and then identify a major problem with the study.

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