Q.#1(a) According to the journal Chemical Engineering, an important property of a fiber is its water absorbency. A random sample of 30 pieces of cotton fiber was taken and the absorbency on each piece was measured. The following are the absorbency values: 18.71, 21.41, 20.72, 21.81, 19.29, 22.43, 20.17,23.71, 19.44, 20.50, 18.92, 20.33, 23.00, 22.85 ,19.25, 21.77, 22.11, 19.77, 18.04, 21.12, 17.9, 17.9,19.44,19.44, 17.9, 20.33, 28.23, 15.20, 30.00, 29.4. (i) Make a frequency distribution of above sample values. (ii) Compute the 10% trimmed mean. (iii) Using only the values of the mean, median, and trimmed mean, do you have evidence of outliers in the data?
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.
Q.#1(a) According to the journal Chemical Engineering, an important property of a fiber is its
water absorbency. A random sample of 30 pieces of cotton fiber was taken and the absorbency on
each piece was measured. The following are the absorbency values:
18.71, 21.41, 20.72, 21.81, 19.29, 22.43, 20.17,23.71, 19.44, 20.50, 18.92, 20.33, 23.00, 22.85
,19.25, 21.77, 22.11, 19.77, 18.04, 21.12, 17.9, 17.9,19.44,19.44, 17.9, 20.33, 28.23, 15.20, 30.00,
29.4.
(i) Make a frequency distribution of above sample values.
(ii) Compute the 10% trimmed
(iii) Using only the values of the mean, median, and trimmed mean, do you have evidence of
outliers in the data?
(iv) Make a Histogram
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