1. A population of 1,000 students spends an average of $10.50 a day on dinner. The standard deviation of the expenditure is $3. A simple random sample of 64 students is taken.

a.What are the expected value, standard deviation, and shape of the sampling distribution of the sample mean? b.What is the probability that these 64 students will spend a combined total of more than $715.21? c.What is the probability that these 64 students will spend a combined total between $703.59 and $728.45?

ANS:
a.10.5 0.363 normal
b.0.0314
c.0.0794

2.The life expectancy in the United States is 75 with a standard deviation of 7 years. A random sample of 49 individuals is selected.

a.What is the probability that the sample mean will be larger than 77 years? b.What is the probability that the sample mean will be less than 72.7 years? c.What is the probability that the sample mean will be between 73.5 and 76 years? d.What is the probability that the sample mean will be between 72 and 74 years? e.What is the probability that the sample mean will be larger than 73.46 years?

ANS:
a.0.0228
b.0.0107
c.0.7745
d.0.1573
e.0.9389
3.A simple random sample of 8 employees of a corporation provided the following information.

Employee12345678

Age2532264050542223

GenderMMMMFMMF

a.Determine the point estimate for the average age of all employees. b.What is the point estimate for the standard deviation of the population? c.Determine a point estimate for the proportion of all employees who are female.

ANS:
a.34
b.12.57
c.0.25
4. MNM Corporation gives each of its employees an aptitude test. The scores on the test are normally distributed with a mean of 75 and a standard deviation of 15. A simple random sample of 25 is taken from a population of 500.

a.What are the expected value, the standard deviation, and the shape of the sampling...

...Elementary Concepts in Statistics. In this introduction, we will
briefly discuss those elementary statistical concepts that provide the necessary
foundations for more specialized expertise in any area of statistical data analysis. The
selected topics illustrate the basic assumptions of most statistical methods and/or have
been demonstrated in research to be necessary components of one's general
understanding of the "quantitative nature" of reality (Nisbett, et al., 1987). Because of
space limitations, we will focus mostly on the functional aspects of the concepts
discussed and the presentation will be very short. Further information on each of those
concepts can be found in the Introductory Overview and Examples sections of this
manual and in statistical textbooks. Recommended introductory textbooks are:
Kachigan (1986), and Runyon and Haber (1976); for a more advanced discussion of
elementary theory and assumptions of statistics, see the classic books by Hays (1988),
and Kendall and Stuart (1979).
• What are variables?
• Correlational vs.
experimental research
• Dependent vs. independent
variables
• Measurement scales
• Relations between variables
• Why relations between
variables are important
• Two basic features of every
relation between variables
• What is "statistical
significance" (p-value)
• How to determine that a
result is "really" significant
•...

...MBA Business Statistics
Homework 1
Reminders:
1. Due date: Jan-14-2012 (Saturday) in class.
2. Please submit only the hardcopy.
3. Please show the names and ID numbers of all your group members on the cover page. Please also
indicate your session (DSME5110W).
1.
Problem 2.1 (p. 33)
The file P02_01.xlsx indicates the gender and nationality of the MBA incoming class in two
successive years at the Kelley School of Business at Indiana University.
a. For each year, create tables of counts of gender and of nationality. Then create column charts of
these counts. Do they indicate any noticeable change in the composition of the two classes?
b. Repeat part a for nationality, but recode this variable so that all nationalities that have counts of 1
or 2 are classified as Other.
2.
Problem 2.5 (p. 33)
The file DJIA Monthly Close.xlsx contains monthly values of the Dow Jones Industrial Average
from 1950 through 2009. It also contains the percentage changes from month to month. (This file will
be used for an example later in this chapter.) Create a new column for recoding the percentage
changes into six categories: Large negative (< -3%), Medium negative (< -1%, ≥ -3%), Small
negative (< 0%, ≥ -1%), Small positive (< 1%, ≥ 0%), Medium positive (< 3%, ≥ 1%), and Large
positive (≥ 3%). Then create a column chart of the counts of this categorical variable. Comment on its
shape.
3.
Problem 2.6 (p. 55)
The file P02_06.xlsx lists the average time (in...

...Gender Discrimination: A StatisticalAnalysis
Gender discrimination, or sex discrimination, may be characterized as the unequal treatment of a person based solely on that person's sex. .
It is apparent that gender discrimination is pervasive in the modern workplace, however, its presence and effects are often misrepresented and misunderstood. Statistical testing plays an important role in cases where the existence of discrimination is a disputed issue and has been used extensively to compare expected numbers of members of a protected group, to the actual number of members of that protected group that have been involved in a significant employment action. This paper will use statistical testing and analysis, including a multiple regression model, to estimate the effects that various independent variables have upon the dependent variable, salary level.
This analysis utilized a data sample consisting of 46 employees and variables relating to each of those employees. These variables include: gender, age, level of education, length of employment, job type, and weekly salary. Each of these variables is further broken as follows: gender was divided between males and females; age was listed as the age of the employee; education was broken down to reflect the last level of education obtained by the employee, some high school, high school, college, and graduate school; employment length was...

...Assignment #3
Constructing a Methodology for StatisticalAnalysis
Christian Diener
998029324
Anthony Chum
Research Problem
As pollution continues to rise in our cities due to various human activities, the incidence of cancer also seems to be increasing. The study of cancer is important because it is a major health problem in today’s society. Not only is it a significant contributor to deaths all around the world but it also affects our economy as a whole. It affects the economy because people who develop cancer are forced to take off work in order to go through the many treatments of radiation and chemotherapy, which in turn has a severe impact on the economy due to the millions of dollars lost in productivity. It is also a financial burden on people due to them losing their job which makes it harder for them to pay the bills and provide themselves with basic needs. So, overall cancer affects a lot of aspects in people’s lives and not just their own lives. Therefore it is an important issue to study and my research question therefore is: Is there significant difference in health related problems, specifically cancer, amongst residents in different regions of the Greater Toronto Area?
Specific Research Questions
The following are more specific questions based on my general research topic:
Is there a significant difference in the prevalence of cancer between men and women?
* Null Hypothesis: There is no significant difference in...

...Final Project: Statistics II
Descriptive analysis of statistical data
INTRODUCTION
There have always been crimes, from a treachery to an assassination. Happens in every country you can think of, and every government has to deal with it. It is really stressful to try to understand the nature of the crimes: why are they done and where could they happen next. Out of this preoccupation is that we found studies gathering data from communities; we focused on one specific crime: murders.
In several communities, it is thought that the murder rate is somehow related to several factors. For instance, it is common to hear that the murder rate depends on poverty and unemployment. Starting from this hypothesis, the database found to make this analysis relates the number of murders per year per 1,000,000 inhabitants with the number of inhabitants, the percentage of families’ incomes below $5000, and the percentage unemployed.
OBJECTIVE OF THE STUDY
Trying to estimate how many murders will happen in a year in a specific place is difficult, but not impossible. This is why we are using the dataset found with the variables mentioned above, with which we’ll be able to find a formula. So, after this project, if we want to know how many murders will be on a city, for example Monterrey, we’d just plug in the data from that city (the inhabitants, the percentage of families income below $5000, and the percentage unemployed) and we’ll get a...

...StatisticalAnalysis of Experimental Density Data
Abstract
Introduction:
The purpose of the lab was to learn how to calculate density of a material by taking it mass and volume. By performing the experiment, important statistical concepts will be learned, for example standard deviation, mean and random error in order to understand the errors that are committed at taking measurements.
Material and methods:
To measure volume and mass were used a burette and balance. The methods used in this experiment were very basic, the instructions show how to read a burette and a balance; and tells how many significant figures have to use for each device. In order to take mass there was necessary to use a beaker to place the glass beads (the object that was going to be measured), and in order to don’t affect the mass or volume of the glass beads there was used forceps. Another methods used in this lab were how to calculate average, standard deviation, confidence intervals and error in density.
Results:
At taking the average for mass and volume of the beads, the results were 3.3048 g (mass) and 1.325 mL (volume). The density was calculated from those results, which was 2.49 g/mL. Standard deviation of mass was 0.01176 g and for volume 0.013 mL. The Confidence Intervals for the mean were obtained. The 95% CI for mean were ±0.01871 g (mass), ±0.021 mL (volume) and ±0.041 g/mL (density). For the 99% CI for mean were ±0.03434 g (mass), ±0.038...

...to create a multiple regression anlysis for this problem. Please provide as much explanation as you can. Please see attached files.
My research is based on this topic below. The data is attached in the spreadsheet. This is a multiple regression analysis. I have attached a PDF file that explains the case and the spreadsheet version with all the data recorded from the PDF file. Pleas emae sure you include all the graphs, plots and please use megastat software.
Topic:
We want to determine the primary factors that affect property crime rates in the United States. The statisticalanalysis of the data involves multiple-regression analysis.
Questions to answer are:
1. What are the primary determinants of property crimes in the United States?
2. What would you like to know about property crime rates that cannot be answered by this data set?
3. How does population density affect property crime rates? Is this expected?
You will want to prepare a summary of your findings to present to a management team from a national crime department. You will find and explain the regression model using a non technical discussion to explain the important factors affect on the property crime rate.
Answer
Multiple regression analysis can be used to model property crime in United States . The regression model suggested is of the form.
Crimes = b0+b1Pincome + b2Dropout +b3Pubaid+b4density+ b5Kids+...

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