Descriptive Statistics Analysis Team A Wk 4

Descriptive Statistics Analysis Team A Wk 4 - Descriptive...

Info iconThis preview shows pages 1–4. Sign up to view the full content.

View Full Document Right Arrow Icon
Descriptive statistics 1 Descriptive Statistics Analysis July 22, 2010 RES 341 C. Mark Talbot University of Phoenix – North Florida
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Descriptive statistics 2 Descriptive Statistics Analysis This is a part III, and the conclusion, of Team A’s research on finding the best value of a home close to the city. In part I, this team identified the research problem and hypothesis, problem and operational definitions, and the overall purpose of the research: find the best value on a home close to the city. In part II, the team reviewed supporting literature, discussed the design of the sampling and data collection, and identified possible ethical concerns regarding the collection of data. The following will include a data analysis using descriptive statistics and a conclusion of this team’s findings. The descriptive statistics being analyzed and calculated are central tendency, dispersion, and skew. This data will then be displayed using graphical techniques. When calculating the measures of central tendency, dispersion, and skew, we must understand what this means. Central tendency is the average of a data set and is a measure of the middle or expected value of the data set. This will show how clustered the variables are. Central tendency of the data can be measured by the arithmetic mean , the median , and the mode . Statistical measures, such as standard deviation and range , are called measures of spread. They describe how spread out the data is (Sekaran, 2003, p. 396). Dispersion will measure the standard deviation and variance. This is often useful to describe a series of observations in interpreting the data. Small values of measures of dispersion mean that the data are clustered around the mean and the mean represents the data well. Large values of measures of dispersion mean that the mean may not represent the overall data well. Skew is the distribution of the data and it may tail off to the left or right of the median. When the asymmetric tail trends to the positive side of the values, this is considered positive
Background image of page 2
Descriptive statistics 3 skew. When the asymmetric tail trends to the negative side of the values, this is considered negative skew. When the skew is symmetric, meaning zero skew, the distribution in the histogram will be in balance on both sides of the median. The following is the central tendency, dispersion, and skew of the real estate data sheet
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Image of page 4
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 03/15/2011 for the course RES 342 taught by Professor Carey during the Spring '08 term at University of Phoenix.

Page1 / 11

Descriptive Statistics Analysis Team A Wk 4 - Descriptive...

This preview shows document pages 1 - 4. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online