In each of the assignments in this course, you will be dealing with the following scenario: American Intellectual Union (AIU) has assembled a team of researchers in the United States and around the world to study job satisfaction. Congratulations, you have been selected to participate in this massive global undertaking.

The study will require that you examine data, analyze the results, and share the results with groups of other researchers. Job satisfaction is important to companies large and small, and understanding it provides managers with insights into human behavior that can be used to strengthen the company's bottom line.

The data set for the study is a sample of a survey conducted on the population of the American Intellectual Union (AIU). It is available via the following link: Excel 2007 DataSet with DataSet Key which contains the following nine sections of data that will be used throughout our course:

Gender
Age
Department
Position
Tenure
Overall Job Satisfaction
Intrinsic Job Satisfaction—Satisfaction with the actual performance of the job Extrinsic Job Satisfaction—external to the job, for example, office location, your work colleagues, your own office (cubicle/hard walled office, etc), Benefits—Health insurance, pension plan, vacation, sick days, etc.

In the first assignment you are to complete the following:

You will need to examine two of the nine sections of data: one section of qualitative data (choose either Gender or Position) one section of quantitative data (choose either Intrinsic or Extrinsic) Each section should include all data points listed in the column for the variable. The requirements include: Identify the data you selected.

Explain why the data was selected.
Explain what was learned by examining these sets of data. Your analysis should include using Microsoft Excel to obtain...

... |
D. The river/lake where a fish was captured
4. Managers study the number of days per month over the last year that employees in the payroll department called in sick to determine the averages they can expect next year. Collecting the data and determining the averages last year is an example of what type of statistics? Determining the averages they can expect next year is an example of what type of statistics?
A. They are both examples of inferential statistics because averages are inferred in both instances.
B. Inferential statistics; descriptive statistics.
C. They are both examples of descriptive statistics because they deal with analyzing data.
D. Descriptive statistics; inferential statistics.
5. The grades that a random sampling of students in the psychology degree program received over the last decade of "Abnormal Psychology" classes are an example of what statistical concept?
A. The grades are an example of a parameter.
B. The grades are an example of a sample.
C. The grades are an example of a population.
D. The grades are an example of a statistic.
6. What method is used to sample a population so that it is representative of the population?
A. All but the samples that appear to have the lowest and highest values are selected.
B. Samples are chosen at random from the...

...central tendency of the sample.
6. Measures of dispersion: range, the interquartile range, the variance, and the standard deviation. What do these measures tell you about the “spread” of the data? Why is it important to spend time performing basic descriptive statistics prior to conducting inferential statistical tests?
Variance of a sample = S2 = =
Standard Deviation of sample S=
Range is the difference between the highest and the lowest values (250-100) = 150
Interquartile Range takes into consideration the fact that there are data extremes that affect the range. In the case of the data above, most of the values are around the median but two values (250 and 275) are extremes. In this scenario, Interquartile range is a better indication of the dispersion of the distribution
100 100 103 104 105 Q1 107 110 110 114 115 M 115 115 115 115 117 Q2 117 118 120 250 275
• Q1 = (105+107)/2 = 106
• Q2 = (117+117)/2 = 117
• IR = 117-106 =9
It is important to evaluate data and look at the entire picture to determine whether something fits or does not. The fact that we get two measurements that were extreme might be an indication that something may have gone wrong. Descriptive statistics in such a case becomes instrumental in our analysis
Type I and Type II Error: The concept of Type I and Type II Error is critical and will come into play with each statistical test you perform. Discuss the implications of...

...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
descriptive statistics. 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 infer the...

...Trajico, Maria Liticia D.
BSEd III-A2
REFLECTION
The first thing that puffs in my mind when I heard the word STATISTIC is that it was a very hard subject because it is another branch of mathematics that will make my head or brain bleed of thinking of how I will handle it. I have learned that statistic is a branch of mathematics concerned with the study of information that is expressed in numbers, for example information about the number of times something happens. As I examined on what the statement says, the phrase “number of times something happens” really caught my attention because my subconscious says “here we go again the non-stop solving, analyzing of problems” and I was right. This course of basic statistic has provided me with the analytical skills to crunch numerical data and to make inference from it. At first I thought that I will be alright all along with this subject but it seems that just some part of it maybe it is because I don’t pay much of my attention to it but I have learned many things. I have learned my lesson.
During our every session in this subject before having our midterm examination I really had hard and bad times in coping up with this subject. When we have our very first quiz I thought that I would fail it but it did not happen but after that, my next quizzes I have taken I failed. I was always feeling down when in every quiz I failed because even though I don’t like this...

...Organization of Terms
Experimental Design
Descriptive
Inferential
Population
Parameter
Sample
Random
Bias
Statistic
Types of
Variables
Graphs
Measurement scales
Nominal
Ordinal
Interval
Ratio
Qualitative
Quantitative
Independent
Dependent
Bar Graph
Histogram
Box plot
Scatterplot
Measures of
Center
Spread
Shape
Mean
Median
Mode
Range
Variance
Standard deviation
Skewness
Kurtosis
Tests of
Association
Inference
Correlation
Regression
Slope
y-intercept
Central Limit Theorem
Chi-Square
t-test
Independent samples
Correlated samples
Analysis-of-Variance
Glossary of Terms
Statistics - a set of concepts, rules, and procedures that help us to:
organize numerical information in the form of tables, graphs, and charts;
understand statistical techniques underlying decisions that affect our lives and well-being; and
make informed decisions.
Data - facts, observations, and information that come from investigations.
Measurement data sometimes called quantitative data -- the result of using some instrument to measure something (e.g., test score, weight);
Categorical data also referred to as frequency or qualitative data. Things are grouped according to some common property(ies) and the number of members of the group are recorded (e.g., males/females, vehicle type).
Variable - property of an object or event that can take on different values. For example, college major...

...Professor Dumonceaux
Descriptive Statistics Paper
2 June 2014
Finding a New Home
According to Trochim, “Descriptive statistics 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 factors include interest...

...
Business Analytics: Unit 1: Descriptive Statistics and Mathematical Foundations
Kaplan University
March 23, 2014
Descriptive Statistics and Mathematical Foundations
Part I: Pie Chart & Bar Graph
This information regards T-100 Domestic Market’s boarding information during the previous year for the top seven airlines in the United Sates. According to the data Southwest Airlines boarded 81.1 million; Delta Airlines, 79.4 million; American Airlines, 72.6 million; United Airlines, 56.3 million; Northwest Airlines, 43.3 million; U.S. Airways, 37.8 million, and Continental Airlines, 31.5 million (KU, 2014).
This is ungrouped data that needs to be grouped into a pie chart and a bar graph. The bar graph and pie chart both lists nonmetric (qualitative) descriptive statistics. The descriptive statistics are called, ordinal statistics which rank each airline from highest to lowest or lowest to highest annual boarding information (Black, 2012). The pie chart and bar graph summarizes the top seven airlines previous years boarding data. First, I will discuss the pie chart. The pie chart below shows the percentage breakdown of each airline’s annual boarding information. Each of the breakdowns represents the magnitude of the whole pie chart in percentages (Black, 2012). As you will notice that the leaders in the airline industry is Southwest and Delta Airlines with 20 percent followed by American...

...The History of statistics can be said to start around 1749 although, over time, there have been changes to the interpretation of the word statistics. In early times, the meaning was restricted to information about states. This was later extended to include all collections of information of all types, and later still it was extended to include the analysis and interpretation of such data. In modern terms, "statistics" means both sets of collected information, as in national accounts and temperature records, and analytical work which require statistical inference.
Statistical activities are often associated with models expressed using probabilities, and require probability theory for them to be put on a firm theoretical basis: see History of probability.
A number of statistical concepts have had an important impact on a wide range of sciences. These include the experiments and approaches to statistical inference such as Bayesian inference, each of which can be considered to have their own sequence in the development of the ideas underlying modern statistics.
The term statistics is ultimately derived from the New Latin statisticum collegium ("council of state") and the Italian word statista ("statesman" or "politician"). The German Statistik, first introduced by Gottfried Achenwall (1749), originally designated the analysis of data about the state, signifying the "science of state" (then called political...