The paired data below consist of the test scores of 6 randomly selected students and the number of hours they studied for the test Hours Scores 5 10 86 4 69 6. 10 9 64 86 59 87 16. What can be said about the relationship between the number of hours and score obtained A. Negative, weak correlation B. Negative, strong correlation C. Positive, weak correlation D. Positive strong correlation 17. Which is the y intercept of the regression line A. 1.067 B. 67.349 C. 0.2242 D. 0.0503

The paired data below consist of the test scores of 6 randomly selected students and the number of hours they studied for the test Hours Scores 5 10 86 4 69 6. 10 9 64 86 59 87 16. What can be said about the relationship between the number of hours and score obtained A. Negative, weak correlation B. Negative, strong correlation C. Positive, weak correlation D. Positive strong correlation 17. Which is the y intercept of the regression line A. 1.067 B. 67.349 C. 0.2242 D. 0.0503

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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Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

The paired data below consist of the test scores of 6 randomly selected students and the
number of hours they studied for the test
Hours
10
4
6.
10
Scores
64
86
69
86
59
87
16. What can be said about the relationship between the number of hours and score
obtained
A. Negative, weak correlation
B. Negative, strong correlation
C. Positive, weak correlation
D. Positive strong correlation
17. Which is the y intercept of the regression line
A. 1.067
B. 67.349
C. 0.2242
D. 0.0503

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