Descriptive Statistics Paper
By
September 27, 2010

In this paper Team B will examine the data that we have collected and we will draw a conclusion based on your findings, to get to the conclusion we will analyze the data using descriptive statistics, we will calculate the measures of central tendency, and dispersion, we will also show all the information with graphics and tables for a better understanding of the date, after all these steps are executed we will draw our conclusion. Data Analysis Using Descriptive Statistics

Through this paper, Team B will use the philosophy of descriptive statistics to describe the main feature of the collection of data quantitatively (Main PS 1995). Descriptive statistics will provide simple summaries about the samples and the measures. In essence, we will show a summary of the data that the team has collected. Some of the ways that we will show the data collected will be in the form of first central tendency which is the distribution locates the center of a distribution of values. The three types of the central tendency are the mean, the median and the mode. Secondly, we will look at the dispersion which is the spread of values around the central tendency (Dodge 2003). The standard deviation is a more accurate way of measuring the dispersion. Thirdly, the use of graphics and tables to illustrate the data collected in a visual background. Fourthly there is the frequency distribution. In the frequency distribution is a summary of the ranges of values. Frequency distribution can be shown by the team in graphic or tables that will be presented. Finally the use of the histogram will be depicted in the team analysis of the data that was collected.

...Professor Dumonceaux
DescriptiveStatisticsPaper
2 June 2014
Finding a New Home
According to Trochim, “Descriptivestatistics are used to describe the basic features of the data in a study. They provide simple summaries about the sample and the measures. Together with simple graphics analysis, they form the basis of virtually every quantitative analysis of data” (Trochim, 2006). For many years, many studies and researches have been done in real estate market. Buyers need to conduct researches to decide which house they will purchase. Buyers’ concerns include the price of the house, the number of bedrooms, and location. Real estate agents need to gather all the necessary information to provide their services to buyers. Additionally, the agents must be able to predict what types of houses are most likely to sell. In this paper, I will provide the summary of what I have been studying. The paper will include the measure of central tendency, dispersion, and skew for data. In addition, this paper will also contain graphic data as well as tabular data to demonstrate my findings and studies. In the end, conclusion will present whether my research findings answered the problem statement or if more research may be needed.
Examining the data collected for the current real estate market desires, following are the conclusions based on its findings. There are many key...

...DescriptiveStatisticspaper
RES/341
July 24, 2011
DescriptiveStatisticspaper
The information below is a continuance of week two, week three, and on week four. The previous assessment in week two on “real estate research” for thinking of hypothesis on home values in Alvarado, Texas. The evaluating on real estate prices reveals a purpose of this research paper and its importance findings. The discoveries include problem definition, and on variables.
The next assessment was on week three on “data collection” on reviewing literatures, sampling design, and on any ethical concerns with collection data on the same topic. A summary was assembled in week three on terms of population, sampling size, and factors on real estate. This research found house prices to change in each different region.
This is week four paper on “descriptivestatistics” on real estate in Alvarado, Texas. The information below will consist of; data analysis, data using graphic and tabular techniques, and on skew values, histogram measures, and on central tendency.
The Central tendency is the measures of numerical summaries used to summarize data with a one number. The most common used are mode, mean, and median. The Hypothesis is "homes more or less expensive fifteen miles away from the center of the city"? The comparison will come from the City of...

...DescriptiveStatistics: Real Estate
University of Phoenix
RES/341 Research and Evaluation I
DescriptiveStatistics: Real Estate
Does having a pool increase the price of houses that have the same number of bedroom? In order to answer that question, we divided our data set into two groups; houses with 1 to 3 bedrooms and houses with 4 and more bedrooms. We then compared the prices of houses with a pool to houses without a pool in each group. Different calculations were used to determine the central tendency, dispersion, and the skew of our data. The central tendency helps to simplify data and also to predict future results. We can use diverse calculations to measure it such as the mean, mode, and median. According to our sample of houses with 1 to 3 bedrooms, the mean price was higher of $4,060 for houses without a pool than with a pool. The same rule applies to houses with more than 4 bedrooms, but with a larger difference of $51,170. Another way we used to calculate the central tendency is by finding the median. The medians are also higher in each group for houses without a pool than those with a pool.
To better answer the above question, we also analyzed the skewness of our data in the two groups. . If we look at the two groups, houses with 1 to 3 bedrooms and houses with 4 or more bedrooms, the data seems to be skewed to the right because the mean is larger than the median. However, due to the...

...Running head: DESCRIPTIVESTATISTICSPAPERDescriptiveStatisticsPaper
Mickey Gahan, Tony Goss, Gerry Camacho and Rob Jacobson
University of Phoenix
Research Process Paper
Few sports have had the social impact that baseball has had over the years. Baseball has long been the all-American pastime. Baseball parks in most major cities across the U.S. attract families including children with dreams of becoming a baseball player. Although ballpark attendance is near 75 million, the cost to operate a major league team is substantial. Salaries alone for 2005 were over 2 billion (University of Phoenix, 2004). This number has increased nearly five-fold over the previous 10 years (USA Today, 2008). People pay to see the best athletes in all sports, not just baseball. Baseball owners analyze data to determine if paying their players higher salaries will pay off by increasing the attendance in ballparks. The data collected in the Major League Baseball Data set is typical data which owners will analyze to determine if paying higher salaries will increase overall profitability.
Purpose of Research
The purpose of this research is to determine whether or not increasing the budget for player salaries will increase the attendance in ballparks. Baseball is not unlike any other business where the name...

...Descriptive and Inferential StatisticsPaper
PSY 315
Descriptive and Inferential Statistics
Whether doing original research or conducting literature reviews, one must conclude what a powerful and versatile tool statistics are in the hands of researchers. From basic statistics such as data description, to using complex statistical methods to foresee future patterns or strengthen scientific claims about current climates, the role of statistics in research cannot be taken lightly and is essential in almost any field, especially in psychology. The statistical method is divided into two main branches called descriptive and inferential statistics. Descriptivestatistics is a summary of information and the data presented is easily understood. Inferential statistics are much more detailed and are used to draw conclusions about hypotheses or determine probabilities of an outcome. Both allow researchers to describe, graph and present data for a general audience or more technical for the professionals. Without statistics, researchers lose that vital tool that allows them to move from hypothesis to conclusion.
The ability to describe data is an essential asset that comes with statistics. Once strong, reliable, and valid data is collected by the researcher, he or she must...

...DescriptiveStatisticsDescriptivestatistics is the analysis of data that summarize data in a way such that, meaningful patterns emerge from the data. Descriptivestatistics do not allow us to reach to the conclusions beyond the data we have analyzed regarding any hypotheses we might have made. They simply describe our data.
Measures of Central Tendency: these are ways of describing the central position of a frequency distribution for a group of data through:
Mode: Sum of all observations divided by the number of observations.
Median: Middle of data. Use with ordinal data or when data contains outliners.
Mean: Most frequent observation. Use with nominal data.
Measures of Spread: these are ways of summarizing a group of data by describing how spread-out the scores are. Statistics available to describe the spreads includes:
Range: Difference between the values of the maximum and minimum observation
Quartiles: more useful than range. Often used with median
Absolute deviation: average of distance of an observation of a distribution from its mean
Variance: takes deviation from Mean
Standard deviation: positive square root of variance
SPSS Software to Measure of Central Tendencies
IBM SPSS Statistics (formerly known as Statistical Package for the Social Sciences) is a popular program for statistical analysis. The base software includes...

...The housing market was once known as the biggest money making industry in the United States. Housing, which was the way our economy made the majority of their money, is now contributing less to the economic expansion. The decline in the housing market has raised many concerns throughout the entire country. This paper provides statistics on the United States population housing market, economy, demographical characteristics, demographical area and the large amount vacant property. Included in this research document are analysis of data sets, charts and graph to help interpret the housing crisis.
Research Problem
The purpose of this research is to determine why the housing market is in a downfall and if there is a way to get homeowners to see the value of their property. Many question the reason of the downfall and who does it affect. The one thing we know for sure is that the economic recession has left a big mark on society in the real estate industry.
Descriptivestatistics
The measures of central tendency can be measured by arithmetic mean, median and mode. The most common of the three is the arithmetic mean. Since the United States population has over one million people data collected from a large population can result in a 95% confidence level. Based on a survey done in the United States, at least three homeowner out of 1,000 are losing their homes to foreclosure. The arithmetic mean is a list of numbers...

...
DescriptiveStatistics
QNT/561
September 5, 2014
DescriptiveStatistics Interpretation
Measuring productivity is paramount for the successful organization; in terms of profitability and progressively growing the business. The data was significantly skewed. Fifty five subjects were randomly selected. Their ages were between 19 and 55 years, with a mean of 37.84, mean of 41 and standard deviation of 9.11. The nurses work shifts varied from morning, mid shift, and overnight. Meade Medical Center strongly believes a 95% population productivity is affected by nurses age and work shift.
Descriptivestatistics
Wage
count
55
mean
33,320.55
sample standard deviation
7,753.39
sample variance
60,115,073.77
minimum
19435
maximum
44975
range
25540
confidence interval 95.% lower
31,271.47
confidence interval 95.% upper
35,369.62
margin of error
2,049.08
z
1.96
1st quartile
27,980.00
median
33,425.00
3rd quartile
40,387.50
interquartile range
12,407.50
mode
19,435.00
low extremes
0
low outliers
0
high outliers
0
high extremes
0
Descriptivestatistics
Age
count
55
mean
37.84
sample standard deviation
9.11
sample variance
82.99
minimum
19
maximum
55
range
36...