Running head: Statistics
Statistics
NAME
BUS308: Statistics for Managers (BAM1714A)
Paul Verlasky
May 8, 2017
Statistics
Statistic
In examining statistics, it is the collection as well as analysis of data to make sense out of
a given sample of data. There
Part One Confidence Intervals
Read Lecture Thirteen. Lecture Thirteen introduces you to confidence intervals. What is a
confidence interval, and why do some prefer them to single point estimates? Ask your
manager what is preferred and why? What are the st
Part One Hypothesis Testing
Read Lecture Four. Lecture Four starts out with the five-step procedure for hypothesis
testing. What is this? What does it do for us? Why do we need to follow these steps in
making a judgement about the populations our samples
The single factor or one way analysis of variance ANOVA is utilized to ascertain significant disparity
between the means of three or more independent groups. It tests the null hypothesis:
= group mean
k = number of groups
An example would be if Frito-Lay
Applied research usually actualizes with a hypothesis that expounds the interaction among
variables or the disparity between means. Effect size is the measure of distinction between
statistical significance and practical significance. Effect sizes formula
I work in the Accounts Receivable Department for DFAS. We are the accounting firm for the DoD. My
area handles all of the United States Marine Corps finance and accounting, specifically appropriations
and intergovernmental transactions involving goods and
Technology has come a very long way in the business world. In 2011 Time did an
interview with V.A. Shiva Ayyadurai, he is the man who had the first copyright for EMAIL,
this man started working on his idea at the age of 14, back in 1978. Doug Aamoth state
TITLE OF PAPER
2
Communication is a very important part how we live our life, not only in the business
world, but also in our personal life. I believe that having good communication skills helps how
you relay information to others. Without communication,
TITLE OF PAPER
2
I have been attending Ashford since 2012 and found that the navigation panel has
been very helpful in getting me around campus. They have made some changes over the
years, added or updated, and even taken a couple away, but most of them a
Running Head: WORKPLACE BULLYINNG, A DAILY OCCURRENCE
Workplace Bullying, A Daily Occurrence
Terri Buchwald
BUS 600
John Johnson
May 15, 2016
1
WORKPLACE BULLYING
2
Bullying is mean and unethical, and should never happen. When I think about bullying
and w
In almost all businesses today there is some form of international or intercultural impacts,
in one way or another. It is very important that we have a good understanding of different
cultural communications. We should know and learn the different type of
Data Type
Nominal Data
Example
Code 0= male & Code 1 = female
Explanation
*Numerical assignment
*These assignments are not
equal to an interval.
* The numbers are equal to an
assignment
*this method is used to make
(counting) classification more
simple
No
Week 2 Lecture 4
(Sampling basics and Hypothesis test)
This week we turn from descriptive statistics to inferential statistics and making decisions
about our populations based on the samples we have. For example, our class case research
question is really
Week 2 Lecture 6
(Additional information on t-tests and hypothesis testing)
Lecture 5 focused on perhaps the most common of the t-tests, the two sample assuming
equal variance. There are other versions as well; Excel lists two others, the two sample assum
Week 3 Lecture 9
Effect Size
When we reject the null hypothesis with an ANOVA test, we have two questions that
arise. The first, which pair of means differs significantly, we have dealt with already. The
second question, similar to what we asked with the
Week 2 Lecture 5
The T-Test
In the previous lecture, we introduced the hypothesis testing procedure, and developed
the first two steps of a statistical test to determine if male and female mean salaries could be
equal in the population where our differenc
Week 1 Lecture 1
Class Approach to Statistics
Statistics is basically a set of tools that allow us to get information out of data sets (we
will get to the more formal definition below). As such, it can be taught as a math class (focusing
on formulas), a l
Week 3 Lecture 7
We have so far seen how we can summarize data sets using descriptive statistics,
showing several characteristics including mean and standard deviation. We also found that if our
data comes from a random sample of a larger population, thes
Week 1 Lecture 3
A second way of looking at data differences or similarities is to consider how likely a
given outcome is. In looking at our data set, we could ask questions such as, what is the
probability (likelihood) of a male or female salary exceedin
Week 1 Lecture 2
In Lecture 1, we focused on identifying the characteristics quantitative, qualitative,
discrete, continuous, NOIR of the data. In this section, we will take a look at how we can
summarize a data set with descriptive statistics, and how we
Week 3 Lecture 8
Excel ANOVA Example
In our on-going investigation of whether or not males and females are paid equally for
equal work, we have come up with contradicting results so far, average salaries are clearly
different but average compa-ratios are
Week 2 Excel Tips
This week we are looking at the t-test for mean differences and the F-test for variance
differences.
T-Test
Two-Sample T. The first test we looked at was the two sample t-test assuming equal
variances. This is selected from the Data tab
1
Economic System Effectiveness
Keshia Hawk
BUS/212
11/07/2016
Aaron Manley
2
Economic System Effectiveness
An economic system is a system of production, resource allocation, and distribution of
goods and services within a society or a given geographic ar
Research paper on statistics
1
Statistics For Manager
Ashley Plata
BUS 308
Instructor Susan Li
December 12, 2016
Research paper on statistics
2
Statistics is derived from Latin word status which imply a group of figures or numbers
which represent informat
Many do not like or trust single point estimates for things they need measured because single
point estimates can be uncertain. Single point estimates are simply just an approximation of a
single quantity or a single numerical value, instead of that of a