Descriptive and Inferential Statistics Paper
Statistics are used for descriptive purposes, and can be helpful in understanding a large amount of information, such as crime rates. Using statistics to record and analyze information, helps to solve problems, back up the solution to the problems, and eliminate some of the guess work. In Psychology there has to be a variable or variables to be organized, measured, and expressed as quantities. Information is usually in the form of a frequency table, histogram, or bar graph to show the increase or decline in occurrences over a period of time. Psychological statistics is used to keep track of behavioral reactions to certain stimuli, and since the human behavior is so unpredictable, psychologists use statistics instead of trying to predict outcomes of situations. Functions of Statistics

Understanding and interpreting data can be difficult if one does not possess the necessary skills to do so. The knowledge of how and why statistics are used is a very important first step to gaining these skills. The following few paragraphs will offer an explanation of the functions of statistics, which will describe how different types of statistics are used to make sense of data that can sometimes be confusing. Both descriptive and inferential statistics serve the same basic functions. The main functions of statistics are to organize and interpret data and to allow one to form hypotheses (Weinclaw, 2008). Statistics help to make sense of data by allowing one to organize and manipulate the data to come to a conclusion. This allows people to gain a better, although not perfect, understanding of phenomena occurring in the real world. Instead of yielding exact results statistics provide probabilities, which allow one to make generalizations about a whole population based on data gathered through surveys or samples of a population. Thus statistics are used to suggest a degree of...

...Professor Dumonceaux
DescriptiveStatistics Paper
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 factors to consider when purchasing a home. Some of the...

...Association [ASA], 2008). Statistics is a division of mathematics that centers on the collection and evaluation of data, which can be drawn upon to make conclusions (Aron, Aron, & Coups, 2006, 2). Two branches of statistics exist, including descriptive and inferential domains. Extrapolation beyond the data is where the real difference emerges. Indeed, these two subcategories vary in function and definition. However, a relationship exists betweendescriptive and inferential statistics, irrespective of the distinction in purpose and meaning.
The function of statistics is the "collecting, analyzing, presenting, and interpreting of data (Statistic, 2008). Statistics have become a valuable tool that many fields use which include but are not limited to business, healthcare, politics, sports, gambling, and all sciences. The government census reports that keep track of the population and the economics of everyday life that is played out on Wall Street and the stock market are two examples of where statistics influence every individual. In psychology statistical methods are used on the data collected regarding a theory or question about human and animal behavior in order to discover the truth about the behavior. For example, a research study on the effects of stress levels of a student and how well the student performs on a test. Through the collection of...

...of 1000 flights and proportions of three routes in the sample. He divides them into different sub-groups such as satisfaction, refreshments and departure time and then selects proportionally to highlight specific subgroup within the population. The reasons why Mr Kwok used this sampling method are that the cost per observation in the survey may be reduced and it also enables to increase the accuracy at a given cost.
TABLE 1: Data Summaries of Three Routes
Route 1
Route 2
Route 3
Normal(88.532,5.07943)
Normal(97.1033,5.04488)
Normal(107.15,5.15367)
Summary Statistics
Mean
88.532
Std Dev
5.0794269
Std Err Mean
0.2271589
Upper 95% Mean
88.978306
Lower 95% Mean
88.085694
N
500
Sum
44266
Summary Statistics
Mean
97.103333
Std Dev
5.0448811
Std Err Mean
0.2912663
Upper 95% Mean
97.676525
Lower 95% Mean
96.530142
N
300
Sum
29131
Summary Statistics
Mean
107.15
Std Dev
5.1536687
Std Err Mean
0.3644194
Upper 95% Mean
107.86862
Lower 95% Mean
106.43138
N
200
Sum
21430
From the table above, the total number of passengers for route 1 is 44,266, route 2 is 29,131 and route 3 is 21,430 and the total numbers of passengers for 3 routes are 94,827.
Although route 1 has the highest number of passengers and flights but it has the lowest means of passengers among the 3 routes. From...

...Running head: DESCRIPTIVE AND INFERENTIAL STATISTICS
1
Descriptive and Inferential StatisticsDESCRIPTIVE AND INFERENTIAL STATISTICS
2
Descriptive and Inferential StatisticsDescriptive and inferential statistics are incredibly similar forms of research testing within psychology. Each seeks to analyze, describe, and possibly predict a population’s behavior. As with psychology itself, statistical analysis within psychology began as a philosophy (Goodwin, 2008). This philosophy quickly turned to a scientific pursuit, again mirroring psychology itself. A person observes, and wonders why that event occurred. That person makes a guess, known as forming a hypothesis, then he or she observes the situation again making small changes to test the theory. Once the determination that the behavior or occurrence is prevalent in a population for which the statistical study is relevant it is given a level of probability (A. Aron, E. Aron, & Coups, 2009). Statistics has two branches descriptive and inferential, and both branches use fundamental concepts as measurements of predictability. The predictability or probability of an event or behavior is determined through values, variables, and scores. Statistics would be redundant if data given by considerable surveys’ and testing were simple to...

...
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...

...Descriptive and Inferential Statistics
Statistical methods in psychology have two main branches, which are descriptive and inferential. They each play a major part in the data that is collected for research and other studies. This paper will show the functions of statistics, how descriptive and inferential statistics are defined and the relationship between the two.
Statistics is a necessary tool in psychology. It provides data for research studies as well as providing background information and support. Without it, understanding the various aspects of psychology and what causes disorders and behaviors would be almost impossible. Scientific, social, and economic studies use statistics in one form or another (Anand, 2013). These disciplines make use of observations, facts and figures, enquiries, and experiments using statistics and statistical methods (Anand, 2013).
Statistics presents facts in a simple form for researchers and psychologists to understand the findings from a research study. It reduces the complex nature of data, especially raw data. Statistics are put into various graphs or diagrams to make data more accessible and intelligible. When statistics are put into a graph, it helps draw inferences and aids in interpretation. Another function of statistics is allowing different sets...

...DescriptiveStatistics
1.1 Descriptive vs. Inferential
There are two main branches of statistics: descriptive and inferential. Descriptivestatistics is used to say something about a set of information that has been
collected only. Inferential statistics is used to make predictions or comparisons
about a larger group (a population) using information gathered about a small
part of that population. Thus, inferential statistics involves generalizing beyond
the data, something that descriptivestatistics does not do.
Other distinctions are sometimes made between data types.
• Discrete data are whole numbers, and are usually a count of objects. (For
instance, one study might count how many pets different families own; it
wouldn’t make sense to have half a goldfish, would it?)
• Measured data, in contrast to discrete data, are continuous, and thus may
take on any real value. (For example, the amount of time a group of children
spent watching TV would be measured data, since they could watch
any number of hours, even though their watching habits will probably be
some multiple of 30 minutes.)
• Numerical data are numbers.
• Categorical data have labels (i.e. words). (For example, a list of the products
bought by different families at a grocery store would be categorical
data, since it would go...

...techniques.
Firstly we look at data analysis. This approach starts with data that are manipulated or processed
into information that is valuable to decision making. The processing and manipulation of raw
data into meaningful information are the heart of data analysis. Data analysis includes data
description, data inference, the search for relationships in data and dealing with uncertainty
which in turn includes measuring uncertainty and modelling uncertainty explicitly.
In addition to data analysis, other decision making techniques are discussed. These techniques
include decision analysis, project scheduling and network models.
Chapter 1 illustrates a number of ways to summarise the information in data sets, also known as
descriptivestatistics. It includes graphical and tabular summaries, as well as summary measures
such as means, medians and standard deviations.
Uncertainty is a key aspect of most business problems. To deal with uncertainty, we need a basic
understanding of probability. Chapter 2 covers basic rules of probability and in Chapter 3 we
discuss the important concept of probability distributions in some generality.
In Chapter 4 we discuss statistical inference (estimation), where the basic problem is to estimate
one or more characteristics of a population. Since it is too expensive to obtain the population
information, we instead select a sample from the population and then use the information in the
sample to...