There are 505 females involved in this case study out of 850 cases. There are 345 males observed in this case study.

Categorical: Class

Out of the 850 cases, 110 are Freshman and 210 are Juniors. 279 are Seniors and 251 are Sophomore.

Categorical: Major

Quantitative: HSP

The graph is skewed to the left and it’s unimodal because it’s only one mass or one “hump.” There are no outliers, everything is close to each other and the graph is continuous.

Categorical: Residency

Of the 850 cases, 227 are nonresident. 623 are residents.

Categorical: Type

Of the 850 cases, 767 are new. 2 had to be readmitted and 81 are transfers.

Quantitative: English

Of the 850 cases, the highest score was in-group 22. The lowest scores were in group 13, 35 and 36 with a score of 1. It’s unimodal and there are outliers. The graph is continuous. Nonskewed, symmetrical graph.

Quantitative: Math

This graph is unimodal. It has outliers. The highest score was an 82 in group 22. The graph is continuous.

Categorical: College

A majority of the cases go to college for A&S. The least amount being in Nursing.

Quantitative: GPA

The graph is unimodal. It’s skewed to the left. Nonsymmetrical. It’s discrete because there is a cap to the GPA.

Quantitative: Age

The graph is unimodal. Majority of the cases age average at around 21 or 22. The graph is also discrete. It’s symmetric and nonskewed.

Quantitative: Credits

The graph is nonskewed, and asymmetrical. It’s multimodal, showing multiple fluctuations.

Quantitative: Comp

The graph is symmetrical, skewed to the right. It’s unimodal and discrete.

...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...

...Types of Variables
Binary variable
Obsevations (i.e., dependent variables) that occur in one of two possible states, often labelled zero and one. E.g., “improved/not improved” and “completed task/failed to complete task.” Usually an independent or predictor variable that contains values indicating membership in one of several possible categories. E.g., gender (male or female), marital status (married, single, divorced, widowed). The categories are often assigned numerical values used as lables, e.g., 0 = male; 1 = female. Synonym for nominal variable. A variable that obscures the effects of another variable. If one elementary reading teacher used used a phonics textbook in her class and another instructor used a whole language textbook in his class, and students in the two classes were given achievement tests to see how well they read, the independent variables (teacher effectiveness and textbooks) would be confounded. There is no way to determine if differences in reading between the two classes were caused by either or both of the independent variables. A variable that is not restricted to particular values (other than limited by the accuracy of the measuring instrument). E.g., reaction time, neuroticism, IQ. Equal size intervals on different parts of the scale are assumed, if not demonstrated. Synonym for interval...

...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 characteristics of the population.
In Chapter 5 we look at the topic of regression analysis which is used to study relationships
between variables.
In Chapter 6 we study another type of decision making called decision analysis where costs and
proﬁts are considered to be important. The problem is not whether to accept or reject a statement
but to select the best alternative from a list of several possible decisions....

...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 the sample of 1000 flights, route 1 has 500 flights which carries a sample mean of 88.532 passengers; route 2 has 300 flights which carries a sample mean of 97.103 passengers and route 3 has 200 flights which carries a sample mean of 107.15 passengers. Hence the mean number of passengers in route 1 is lower than route 2 and route 3.
Reasons for Choosing Histogram
Histogram can be easily compared by identifying where the maximum, minimum and medium among the 3 different routes. In this case study, we would like to compute the total number of passengers for...

...generate statistics which are used by teachers to analyse a student’s performance and development of theories to explain the differences in performance.
The Standard 3 class is where the transition from junior to senior level occurs where teachers expect the transference of concrete to abstract thinking would have occurred.
A common theory by many primary school teachers is ‘Students perform better in Mathematics than Mental math. Mental math is something that has to be developed and involves critical thinking. Mental math requires quick thinking and the student must solve the problem in their minds whereas in regular mathematics, the problem can be solved visually. Therefore, teachers should take these factors into consideration while testing and marking students in these areas.’
In this study, the statistics of 30 students of a standard 3 class of San Fernando Boys’ Government School will be analysed to determine the truth of this theory.
DATA COLLECTION METHODS
Mathematics and mental mathematics marks of term 1 of the class of 2013 were obtained from a Standard 3 teacher of San Fernando Boys’ Government School.
The marks were divided into the form:
Mathematics Marks, x
Mental Mathematics marks, y
DATA PRESENTATION AND ANALYSIS
Sample number
Marks earned (x)
x²
1
70
4900
2
86
7396
3
49
2401
4
66
4356
5
94
8836
6
68
4624
7
92
8464
8
96
9216
9
76
5776
10
71
5041...

...
MBA 501A – [STATISTICS]
ASSIGNMENT 4
INSTRUCTIONS: You are to work independently on this assignment. The total number of points possible is 50. Please note that point allocation varies per question. Use the Help feature in MINITAB 16 to read descriptions for the data sets so that you can make meaningful comments.
[10 pts] 1. Use the data set OPENHOUSE.MTW in the Student14 folder. Perform the Chi
Square test for independence to determine whether style of home and location are are related. Use α = 0.05. Explain your results.
Pearson Chi-Square = 37.159, DF = 3, P-Value = 0.000
Likelihood Ratio Chi-Square = 40.039, DF = 3, P-Value = 0.000
The P value associated with out chi square is 0.00 and the Alpha level is 0.05 so we reject the null hypothesis. The P- value is less than the alpha level. So, we conclude that style of homes and locations are not related.
[10 pts] 2. Use the data set TEMCO.MTW in the Student14 folder. Perform the Chi
Square test for independence to determine whether department and gender are related. Use α = 0.05. Explain your results.
Pearson Chi-Square = 1.005, DF = 3, P-Value = 0.800
Likelihood Ratio Chi-Square = 1.012, DF = 3, P-Value = 0.798
The P-value associated with out chi square is 0.800 and the Alpha level is 0.05 we can see that we are unable to reject the null hypothesis. The P- value is greater than the alpha level. So, we conclude that departments and gender are related..
[30 pts] 3. Use the data set...

...Statistics 1
Business Statistics
LaSaundra H. – Lancaster
BUS 308 Statistics for Managers
Instructor Nicole Rodieck
3/2/2014
Statistics 2
When we hear about business statistics, when think about the decisions that a manager makes to help make his/her business successful. But do we really know what it takes to run a business on a statistical level? While some may think that businessstatistics is too much work because it entails a detailed decision making process that includes calculations, I feel that without educating yourself on the processes first you wouldn’t know how to imply statistics. This is a tool managers will need in order to run a successful business. In this paper I will review types of statistical elements like: Descriptive, Inferential, hypothesis development and testing and the evaluation of the results. Also I will discuss what I have learned from business statistics.
My description of Descriptive statistics is that they are the numerical elements that make up a data that can refer to an amount of a categorized description of an item such as the percentage that asks the question, “How many or how much does it take to “ and the outcome numerical amount. According to “Dr. Ashram’s Statistics site” “The quantities most commonly used to measure the dispersion of the values about...

...STAT 600 Statistics and Quantitative Analysis
PROJECT: Stock return estimation
The project must be done by 6-15 a.m. October, 16th. You should submit your projects before the class begins. This is a group project. Read the course outline for general guidelines. Good luck!
The project is closely related to Lectures 1-5 of the class.
Today is September 15, 2013 and you have just started your new job with a financial planning firm. In addition to studying for all your license exams, you have been asked to review a portion of a client’s stock portfolio to determine the risk/return profiles of 12 stocks in the portfolio. Unfortunately, your small firm cannot afford the expensive databases that would provide all this information with a few simple keystrokes, but that’s why they hired you. Specifically, you have been asked to determine the monthly average returns and standard deviations for the 12 stocks for the past five years.
The stocks (with their symbols in parentheses) are:
Apple Computer (AAPL) Hershey (HSY)
Archer Daniels Midland (ADM) Motorola (MOT)
Boeing (BA) Procter and Gamble (PG)
Citigroup (C) Sirius XM radio (SIRI)
Caterpilar (CAT) Wal-Mart (WMT)
Deere&Co. (DE)...