9.1. 3.The accompanying table shows the ages (in years) of 11 children and the numbers of words in their vocabulary. Complete parts (a) through (d) below. X Y 0 0 1 500 2 600 4 1200 6 1800 8 2400 10 3000 3(b) Calculate the sample correlation coefficient r. r= (c) Describe the type of correlation, if any, and interpret the correlation in the context of the data. There is (1) linear correlation. Interpret the correlation. Choose the correct answer below. A. Based on the correlation, there does not appear to be any relationship between children's ages and the number of words in their vocabulary. B. Aging causes the number of words in children's vocabulary to increase. C. As age increases, the number of words in children's vocabulary tends to decrease. D. Based on the correlation, there does not appear to be a linear relationship between children's ages and the number of words in their vocabulary E. Aging causes the number of words in children's vocabulary to decrease. F. As age increases, the number of words in children's vocabulary tends to increase. (d) Use the table of critical values for the Pearson correlation coefficient to make a conclusion about the correlation coefficient. Let α=0.01. The critical value is nothing. Therefore, there (2) sufficient evidence at the 1% level of significance to conclude that (3) between children's ages and the number of words in their vocabulary.
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.
9.1.
3.The accompanying table shows the ages (in years) of 11
children and the numbers of words in their vocabulary. Complete parts (a) through (d) below.
X Y
0 0
1 500
2 600
4 1200
6 1800
8 2400
10 3000
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