Statistics Homework 1 & 2

● Descriptive summary table

Table 1

Descriptive statistic tables for Height and Weight

Data analysis

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● Descriptive summary table

a. Measures of center: A measure of central is a value that attempts to describe a set of data by identifying the central position of the

dataset. From the descriptive statistic tables of Height and Weight, we can see both the mean and median are close in values for

these two variables. We are familiar with measures of central tendency called the mean, median and mode. Therefore, it can be

inferred that these two datasets are more or less evenly distributed from the lowest to highest values, that is the near bell shape

normal distribution.

b. Measures of variability: As both of datasets are near the bell shape distribution, the Empirical Rule can be applied to them to

provide a range of estimates for the percentage of values. Therefore, weight dataset is more consistent and stable than height

dataset because of smaller standard deviation and closer values from the Empirical Rule calculation. In addition, the range of

height dataset is wider than weight dataset.

c. Kurtosis and Skewness: From the Skewness value, both of these two datasets are fairly symmetrical dataset while height dataset is

more fairly symmetrical than weight dataset as its skewness is much closer to 0. If the kurtosis is close to 0, then a normal

distribution is often assumed. If the kurtosis is less than zero, then the distribution is light tails and is called a platykurtic

distribution which is height datset. If the kurtosis is greater than zero, then the distribution has heavier tails and is called a

leptokurtic distribution which is weight dataset.

Data analysis

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