This chapter describes the various ways descriptive statistics is applied in our
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Question
This chapter describes the various ways descriptive statistics is applied in our daily lives. It explains the numbers and calculations we use to summarize raw data collected in our workplace, or during our leisure activities. It also covers how one can use certain "shortcuts" to determine how one product measures up to its rival. These "shortcuts" are using the formulas for solving the mean and median when looking at large amounts of data. It also discusses how when solving of the mean, one would also need to take in consideration what the standard deviation is of the collected set of data In this chapter, the author uses history as one example of using descriptive statistics. When answering "What is happening to the economic health of America's middle class?", they gathered information from 1980 and compared it to similar data taken in 2010. Once this was done, they measured inflation and also examined wages to explain how one statistician might record the found data to be one way when another one might record it with the variables taken into consideration.Explanation / Answer
This section portrays the different ways expressive insights is connected in our day by day lives. It clarifies the numbers and computations we use to abridge crude information gathered in our working environment, or amid our recreation exercises. It likewise covers how one can utilize certain easy routes to decide how one item measures up to its opponent. These easy routes are utilizing the equations for illuminating the mean and middle when taking a gander everywhere measures of information. It additionally examines how when understanding of the mean, one would likewise need to take in thought what the standard deviation is of the gathered arrangement of information In this section, the creator utilizes history as one case of utilizing graphic measurements. While noting What is occurring to the monetary strength of Americas working class?, they accumulated data from 1980 and contrasted it with comparative information taken in 2010. When this was done, they quantified swelling and furthermore analyzed wages to clarify how one analyst may record the observed information to be one way when another might record it with the factors mulled over.