Objective: To use the statistical data/analysis provided by Fliege & Associates, to make an informed decision in determining which type of property (business) I should have built on recently inherited land in Riverside County California. I will use the descriptive statistical analysis report given on the demographical information for the county, in regards to its population of residents; to compare and contrast to a recent case study involving a similar tract of land in a likewise small community located approximately one hour away in San Diego California.

...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...

...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...

...3
Question 2a 5
Question 2b 6
Question 2c 7
Question 3a 8
Question 3b 8
Question 3c 10
Question 3d 11
Question 4 12
Question 5 14
References 15
Question 1
The sampling method that Mr. Kwok is using is Stratified Random Sampling Method. In this case study, Mr Kwok collected a random sample 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...

...compliments the regular mathematics and therefore both are tested in primary schools. Mathematics is the written application of operation. It teaches students to think clearly, reason well and strategize effectively. Mental Mathematics is the ability to utilise mathematical skills to solve problems mentally. The marks scored by pupils 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’...

...Sarah J. Barnett Mr. W. Gissy Econ 2300/05 February 22, 2005 Case Study 1 – Hamilton County Judges 1. Based on the information provided in the Hamilton County Judges’ case study, the probability of cases being appealed and reversed in the three different courts are: a. For the total cases disposed in the Common Pleas Court there is a 0.1129 probability of a case being appealed and reversed. b. For the total cases disposed in the Domestic Relations Court there is a 0.1604 probability of a case being appealed and reversed. c. For the total cases disposed in the Municipal Court there is a 0.2080 probability of a case being appealed and reversed. 2. The probability of a case being appealed, per judge, is: a. Common Pleas Court: Judge Fred Cartolano Thomas Crush Patrick Dinkelacker Timothy Hogan Robert Kraft William Mathews William Morrissey Norbert Nadel Arthur Ney Jr. Richard Niehaus Thomas Nurre John O'Connor Robert Ruehlman J. Howard Sundermann Jr. Ann Marie Tracey Ralph Winkler b. Domestic Relations Court: Judge Penelope Cunningham Patrick Dinkelacker Deborah Gaines Ronald Panioto (P) of Appeal per Judge 0.002565 0.003166 0.005455 0.002467 (P) of Appeal per Judge 0.045110 0.035291 0.034976 0.030706 0.040472 0.040194 0.039908 0.044272 0.038832 0.040859 0.040333 0.043449 0.045242 0.062827 0.040433 0.028488...

...Prepare a managerial report for the dean of the college that summarizes your assessment of the nature of cheating by business students at Bayview University. Be sure to include the following questions.
1. Develop 95% confidence intervals for the proportion of all students, the proportion of male students, and the proportion of female students who were involved in some type of cheating.
2. Conduct a hypothesis test to determine if the proportion of business students at Bayview University who were involved in some type of cheating is less than that of business students at other institutions as reported by the Chronicle of higher education. The article reported 56% of business students.
3. Conduct a hypothesis test to determine if the proportion of business students at bayview University who were involved in some type of cheating is less than that of non business students at other institutions as reported by the Chronicle of higher education. The article reported 47% non business students.
4. What advise would you give to the Dean based upon your analysis of the data?
Student/Copied from Internet/Copied on Exam/Collaborated on Individual Project/Gender/
1 No No No Female
2 No No No Male
3 Yes No Yes Male
4 Yes Yes No Male
5 No No Yes Male
6 Yes No No Female
7 Yes Yes Yes Female
8 Yes Yes Yes Male
9 No No No Male
10 Yes No No Female
11 No No No Male
12 No Yes Yes Female
13 No No Yes Male
14 No No No Male
15 No Yes Yes Male
16 No No No M ale
17 No No...

...StatisticsCase Study-1
Age Weeks Employed
55 21
30 18
23 11
52 36
41 19
25 12
42 7
45 25
25 6
40 21
25 13
25 11
59 34
49 27
33 18
35 20
a.
Age Weeks Employed
Mean 37.75 Mean 18.6875
Standard Error 2.974195 Standard Error 2.188452
Median 37.5 Median 18.5
Mode 25 Mode 21
Standard Deviation 11.89678 Standard Deviation 8.753809
Sample Variance 141.5333 Sample Variance 76.62917
Kurtosis -1.17143 Kurtosis -0.21626
Skewness 0.337402 Skewness 0.522601
Range 36 Range 30
Minimum 23 Minimum 6
Maximum 59 Maximum 36
Sum 604 Sum 299
Count 16 Count 16
Confidence Level(99.0%) 8.764138 Confidence Level(99.0%) 6.44877
b. 99% confidence interval estimate for mean age of newly hired employees;
37.75 ¡V 8.76 = 28.99
to
37.75 + 8.76 = 46.51
c. Hypothesis:
Decision Rule: Reject Ho if t > t-critical
Do not reject Ho if t < t-critical
t-critical = t0.01,15 =2.602
0.771 < 2.602
Therefore, at a 99% Confidence Level the Null Hypothesis can not be rejected and we can not state that Riverside¡¦s mean duration of employment weeks is any greater than the mean duration of employment weeks within the rest of California.
d. Is there a relationship between the age of a newly employed individual and the number of weeks of employment?
By using a scatter plot and plotting the number of weeks employed in respect to the ages of the workers, you can see that the points are...

...
Case Study: Out-of-Town Brown and the Besieged Probation Supervisor
Case Study: Out-of-Town Brown and the Besieged Probation Supervisor
This case study will examine four parts of out-of-town brown and the besieged probation supervisor. The first is what should Casey’s response be to the reporter concerning the agency’s recommendation. The second is if Casey elects to discuss her officer’s recommendation for some form of intermediate sanction, how can she justify such sanctions in general and in this case specifically. The third covers do you feel that the probation officer’s recommendation based on these facts is correct, why or why not. Lastly, which form of intermediate sanction would appear to hold the most promise for the offender in this case.
Casey’s Response
I would answer the phone and answer question with a brief conversation. I am standing by the decision the probation officer has recommended. The intermediate sanction is proper decision for a 23-year-old man who murdered his stepfather with a knife after suffering many years of physical and mental abuse. The young man had no prior record and had been an incest victim since he was 5 years old; he is considered an otherwise nonviolent person, a low recidivism risk. However, this call that I receiving from you, a well-known veteran local television anchor—a strong crusader in the local...

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