In today’s world, we are faced with situations everyday where Statistics can be applied. In general, Statistics is the science of collecting, organizing, and analyzing numerical data. The techniques involved in Statistics are important for the work of many professions, thus the proper preparation and theoretical background of Statistics is valuable for many successful career paths. Marketing campaigns, the realm of gambling, professional sports, the world of business and economics, the political domain, education, and forecasting future occurrences are all areas which fundamentally rely on the use of Statistics. Statistics is a broad subject that branches off into several categories. In particular, Inferential Statistics contains two central topics: estimation theory and hypothesis testing. The goal of estimation theory is to arrive at an estimator of a parameter that can be implemented into one’s research. In order to achieve this estimator, statisticians must first determine a model that incorporates the process being studied. Once the model is determined, statisticians must find any limitations placed upon an estimator. These limitations can be found through the Cramer-Rao lower bound. Under smoothness conditions, the Cramer-Rao lower bound gives a formula for the lower bound on the variance of an unbiased estimator. Once the estimator is developed, it is tested against the limitations to see if it is valid relative to the model. Lastly, experiments are run using the estimator to test performance. From real data, statisticians are able to decide whether the estimator is incorrect, and in this case, they can go back and find a new estimator. It is important for an estimator to achieve a minimum average error (i.e. minimum variance unbiased estimator). This type of estimator is known to be an efficient estimator because the average error measure is the variance. Other performance measures for estimators include: bias and consistency. An estimator is said...

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Inferentialstatistics
Sampling
* The purpose of sampling is to select a set of elements (sample) from a population that we can use to estimate parameters about the population
* The bigger the sampling, the more accurate our parameters will be.
example:
In the experiment of deciding if CEGL girls are smarter that CEGL boys, which would be your statistical hypothesis?
Hypothesis testing
But now, you already gathered information about a sample
No, you will test if your hypothesis are true or not
Hypothesis testing involves testing the difference between a hypothesized value of a population parameter and the estimate of that parameter, calculated from the sample
example:
If you want to know if CEGL girls are smarter that CEGL boys, you ask a few girls/boys their grades and compare averages, we will use Excel to compare the population and sample means. If the difference is too high, we can’t compare.
In statistics, the hypothesis to be tested is called “null hypothesis” and has the symbol “Ho”
The other option of the hypothesis is the “alternative hypothesis” and its symbol is “Ha”
1 Ho: “There is no difference between (independent variable) and (dependent variable)”
2 Ha: “There is a difference between (independent variable) and (dependent variable)”
example:
In the experiment of deciding if CEGL girls are smarter that CEGL boys, which would be your statistical hypothesis?
Ho:...

...Statistics is the study of the collection, organization, analysis, interpretation, and presentation of data. It deals with all aspects of this, including the planning of data collection in terms of the design ofsurveys and experiments.
The word statistics, when referring to the scientific discipline, is singular, as in "Statistics is an art “This should not be confused with the word statistic, referring to a quantity (such as mean or median) calculated from a set of data, whose plural is statistics ("this statistic seems wrong" or "these statistics are misleading").
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Scope
Some consider statistics a mathematical body of science that pertains to the collection, analysis, interpretation or explanation, and presentation of data while others consider it a branch of mathematics]concerned with collecting and interpreting data. Because of its empirical roots and its focus on applications, statistics is usually considered a distinct mathematical science rather than a branch of mathematics. Much of statistics is non-mathematical: ensuring that data collection is undertaken in a way that produces valid conclusions; coding and archiving data so that information is retained and made useful for international comparisons of official statistics; reporting of results and summarised...

...Contents
Data Analysis: Analyzing Data - InferentialStatisticsInferentialstatistics deal with drawing conclusions and, in some cases, making predictions about the properties of a population based on information obtained from a sample. While descriptive statistics provide information about the central tendency, dispersion, skew, and kurtosis of data, inferentialstatistics allow making broader statements about the relationships between data. Inferentialstatistics are frequently used to answer cause-and-effect questions and make predictions. They are also used to investigate differences between and among groups. However, one must understand that inferentialstatistics by themselves do not prove causality. Such proof is always a function of a given theory, and it is vital that such theory be clearly stated prior to using inferentialstatistics. Otherwise, their use is little more than a fishing expedition. For example, suppose that statistical methods suggest that on average, men are paid significantly more than women for full-time work. Several competing explanations may exist for this discrepancy. Inferentialstatistics can provide evidence to prove one theory more accurate than the other. However, any ultimate conclusions about actual causality must come from...

...InferentialStatistics
Drawing Conclusions based on Samples
Introduction
This chapter introduces how you can use data from a sample to draw conclusions about the larger population from which the sample was taken. Data often arises from the results of a survey of individuals. For example, the management of a fast food chain might be interested in determining the total number of dollars that Baylor students spend each year eating in Waco fast food restaurants. The fast food chain would also like to know the fast food preferences of the Baylor students. Both of these pieces of information would be helpful in estimating how successful a particular fast food chain might be if located near the Baylor campus. The management of the fast food chain probably does not have the time or money to question every single Baylor student. Time and money to question 300 students might be available. Techniques exist for randomly choosing a representative sample of 300 students from the population of the 14,000 Baylor students. An estimate or guess for the total dollars spent by all 14,000 Baylor students per year can be made from the amount spent by the sample of 300 students. You would not expect the estimate to be perfect. There would be some difference between the estimate based on the sample and the unknown total amount spent by all 14,000 students. The difference between the two amounts is called sampling error. The word, “error”, does not...

...Chapter 1 : Introduction
Learning goals
❖ What is meant by Statistics
❖ What is meant by Descriptive Statistics and InferentialStatistics
❖ Difference between Parameter & Statistic
❖ Types of Statistical Inferences
What is meant by Statistics ?
Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting numerical data to assist in making more effective decisions.
Types of Statistics
Descriptive Statistics :
• Methods of organizing, summarizing, and presenting data in an informative way.
InferentialStatistics:
• A decision, estimate, prediction, or generalization about a population, based on a sample.
Population versus Sample
• A population is a collection of all possible individuals, objects, or measurements of interest.
• A sample is a portion, or part, of the population of interest
Parameter and Statistic
• A measure found from the entire population is called a population parameter or simply a parameter. (such as µ, σ, σ²)
• A measure found from analysing sample data is called a sample statistic or simply a statistic (such as x¯, s¯, s²)
Types of Statistical Inferences
It refers to the process of selecting and using a sample statistic to draw inference about a population...

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InferentialStatistics and Findings
Erick Mart
QNT/561
August 25th 2014
Mario LOPEZ
InferentialStatistics and Findings
InferentialStatistic is the process of drawing conclusions from data that are subject to random variation, for example, observational errors or sampling variation. Our team uses inferentialstatistic to compare two groups, which are Melks and DHL. This paper outlines the sampling and data collection procedure used to test the null hypothesis. The null and alternate hypotheses are:
(There is no significant difference in brand awareness based on the marketing channel used).
(There is a significant difference in brand awareness on the basis of the marketing channel used).
Here is an example of the statistics of our results describing the total number of people from minimum age to maximum from ages 35 to 55. Mock data for the independent variables for Melks.
Descriptive statistics
Income
Age
Count
300
300
Mean
56,426.45
45.91
sample standard deviation
3,876.30
7.23
sample variance
15,025,706.87
52.29
Minimum
50000
34
Maximum
60000
55
Range
10000
21
confidence interval 95.% lower
54,135.75
41.64
confidence interval 95.% upper...

...(DoeJXXX0000-1) justified to the left and the page number justified to the right.
Keep a Photocopy or Electronic Copy of Your Assignments: You may need to re-submit assignments if your mentor has indicated that you may or must do so.
Academic Integrity: All work submitted in each course must be the Learner’s own. This includes all assignments, exams, term papers, and other projects required by the faculty mentor. The known submission of another person’s work represented as that of the Learner’s without properly citing the source of the work will be considered plagiarism and will result in an unsatisfactory grade for the work submitted or for the entire course, and may result in academic dismissal.
BTM7103
Dr. Mirza Mutaza
Business Research Methodology
Assignment 5 Exploratory methods
Faculty Use Only
Apply Exploratory Research
Rob Marks
Northcentral University
Dr. Mirza Mutaza
What is naturalistic observation? How does a researcher collect data when conducting naturalistic observation research? Naturalistic observation is normally considered fieldwork or field observation. Naturalistic observation can be used within the social sciences as a study of field research tends to investigate and establish data (Bates & Cozby, 2012, pg. 115). Naturalistic observation has roots grounded in social sciences such as...

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Group Assignment
BusinessStatistics
CBEB1109
Tutorial : Tuesday 11.00am – 12.00pm
Instructor : Dr. Sharifah Latifah Binti Syed A Kadir
Group : Group 2
Group Members :
1.
Kao Wei Jian
CEA 130028
2.
Lim Kin Chun
CEA 130041
3.
Amirul Asyraaf bin Azhar
CEA 130002
4.
Nur Hasfaiza bt Mohd Zaid
CEA 130063
5.
Muhammad Hamdin Zarif Bin Mohd Zaidi
CEA 100062
6.
Lim Sin Pei
CEA 130043
7.
Wong Siew Yen
CEA 130097
1. Of 100 individuals who applied for systems analyst positions with a large firm during the past year, 40 had some prior work experience, 30 had a professional certificate and 20 of them had both work experience and a certificate.
a Determine if work experience and certification are independent events.
Let A = Prior Work experience
B = Professional Certificate
A
A’
Total
B
20
30
50
B’
40
10
50
Total
60
40
100
=
= 0.4
P(A) =
= 0.6
, so it is not an independent event.
b What is the probability that a randomly chosen applicant,
i had either work experience or a certificate?
) =
=
= 0.9
ii has neither work experience nor a certificate?
iii has a certificate if he has some previous work experience?
= 0.33
2. Because of economic conditions, a firm reports that 30 percent if its accounts receivable from other business firms are overdue. If an accountant takes a random sample of 10 such accounts, determine the probability that
p=30% @ 0.3
n=10
X~B(10,0.3)
a. none of the account is overdue
By...