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Correlation between age and weight Name Institutional affiliation Correlation between age and weight Several studies such as epidemiological studies give special regard to age and weight since the variables act as both confounding variables and primary exposure variables. This paper aims at discussing the statistical ways of analyzing the differences in the two variables (age and weight) using hypothetical data. The paper also interprets the various statistical outputs that are computed from the data. Null hypothesis: There is no statistical significance between age and weight Alternative hypothesis: there is a statistical significance relationship between age and weight of bears. Descriptive statistics. Assume a hypothetical data set with a mean age of 43.51 years and mean weight of 182.88 kilograms. This data will help to show how differences between the two variables can be analyzed. An excel spreadsheet will be used to obtain the results, and the paper will attempt to give an interpretation of the results. Other useful characteristics of the two variables are described below. Age Weight Median 34150 Mode 57166 SD33.72121.80 Variance 1137.08714835.53 Differences in variables such as height and weight can be analyzed by using various methods such as correlation coefficients and independent t tests. Correlation refers to the degree of association between two different variables (Ross, 2004). The degree of association is expressed by the correlation coefficient which takes values ranging from +1 and -1. When the correlation coefficient (r) is negative, it means that one variable (either x or y) tends to decrease as the other variable
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