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A researcher wants to determine if body weight is associated with the number foreign countries a person visited. He recruits a random sample of 68 people to take a survey asking respondents to estimate their current body weight and the number of countries visited. What statistical analysis would be most appropriate to evaluate if the two variables are related to each other? ANOVA Pearson's correlation independent samples t-test dependent samples t-test

A researcher wants to determine if body weight is associated with the number foreign countries a person visited. He recruits a random sample of 68 people to take a survey asking respondents to estimate their current body weight and the number of countries visited. What statistical analysis would be most appropriate to evaluate if the two variables are related to each other? ANOVA Pearson's correlation independent samples t-test dependent samples t-test

A First Course in Probability (10th Edition)
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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**Exploring the Relationship between Body Weight and Travel Frequency** A researcher aims to determine if there is an association between body weight and the number of foreign countries a person has visited. This inquiry involves gathering data from a random sample of 68 individuals. Each participant is asked to estimate their current body weight and report the number of countries they have visited. The goal is to identify the most suitable statistical analysis to evaluate the relationship between these two variables. The available statistical methods to consider are: - ANOVA - Pearson’s correlation - Independent samples t-test - Dependent samples t-test **Explanation of the Suitable Statistical Analysis** In this scenario, the most appropriate statistical analysis would be **Pearson’s correlation**. Pearson's correlation coefficient measures the strength and direction of the linear relationship between two continuous variables. Here, it would assess whether there is a significant association between body weight (a continuous variable) and the number of countries visited (another continuous variable).
Transcribed Image Text:**Exploring the Relationship between Body Weight and Travel Frequency** A researcher aims to determine if there is an association between body weight and the number of foreign countries a person has visited. This inquiry involves gathering data from a random sample of 68 individuals. Each participant is asked to estimate their current body weight and report the number of countries they have visited. The goal is to identify the most suitable statistical analysis to evaluate the relationship between these two variables. The available statistical methods to consider are: - ANOVA - Pearson’s correlation - Independent samples t-test - Dependent samples t-test **Explanation of the Suitable Statistical Analysis** In this scenario, the most appropriate statistical analysis would be **Pearson’s correlation**. Pearson's correlation coefficient measures the strength and direction of the linear relationship between two continuous variables. Here, it would assess whether there is a significant association between body weight (a continuous variable) and the number of countries visited (another continuous variable).
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