* Data Analysis Methods
I am using correlation for surveys and observational studies, person correlation if relationship is linear, otherwise Spearman correlation. And get the answer about correlative between per capita income and the percentage of labour force employed in agriculture. * Results

From Figure 1 it appears that there is an association between the percentage of labour force employed in agriculture and per capita income. The points in the scatter plot are irrelevant. When the per capita income increases, the percentage of labour force employed in agriculture decreases.

Figure 1: Scatter/Dot of labour force employed in agriculture Table 1: Summary statistics
Figure 1: Scatter/Dot of labour force employed in agriculture. From Figure 1 there appears to be an association between agriculture and income in 1960. A test of the null hypothesis of no difference in means gave a p-value of 0.001, and the difference in means confidence to lay in the interval units.

* Appendix
Step1: Determine the Parameter of interest.
* When analysing frequency distributions our interest centres on the parameter of interest if an association between per capita income and the percentage of labour force employed in agriculture. * Choose the person correlation coefficient ρ as the parameter of interest. Step2: Write the hypotheses.

* The parameter of interest is the proportion distribution for per capita income and the percentage of labour force employed in agriculture. * Ho: P=0 there is not association between per capita income and the percentage of labour force employed in agriculture. * Ha: p>0 there is association between per capita income and the percentage of labour force employed in agriculture Step3: Specify test criteria.

* Use a T-test with 18 degrees of freedom.
* A significance level of α=0.05 will apply.
Step 4: Computer P-value.
Correlations|
| Per capita income, 1960 ($)| Correlation coefficient rs=-0.795...

...practice
• Misconceptions
o Not simply gathering existing information
o Not merely gathering new data
o Not necessarily the production of something original
o Not always involving a problem
• Knowledge-driven
o Explores
o Speculates
o Describes
o Explains
o Predicts
o Evaluates
• Purposes
o Role expectation
o Current information
o Client perspectives
o Solutions to problems
o Improvements
o Interests
o Evidence-based practice
Research Continuum
Basic
• Usually deals with theoretical
problems
• Conducted in laboratory
settings
• Frequently uses animal subjects
• Carefully controls conditions
• Has limited direct application
•
•
•
•
•
•
Applied
Addresses immediate issues
Conducted in real-world settings
Involves human participants
Has limited control over setting
Has direct value to practitioners
Has ecological validity
2
Characteristics of QUALITY research
1. Identifying & delimiting a problem
2. Searching, reviewing & writing
3. Specifying & defining testable hypotheses
4. Designing to test hypotheses or answer questions
5. Selecting, describing, testing & treating or engaging with participants
6. Analysing & reporting results
7. Discussing meaning & implications
The Research Process
1. Identify a question / issue
2. Consider the question / issue itself & possible ways to answer / solve it
3. Use a valid & reliable method to answer / solve it
4. Reflect on 1, 2 & 3. Then discuss...

...worthy teachers Mr. ABID AWAN and Mr. HASSAN JABBAR who gave us complete attention & guide us regarding the completion of the research proposal.
Table of Content
List of appendixes
Appendix Name of appendix Page No.
A Questionnaire……………………………………………..... 46
List of tables
Table Heading of table Page No.
1 Demographics Analysis…………………………………………..26
2 Normality Analysis…………………………………………….....30
3 Reliability Analysis ……………………………………………...31
4 Exploratory Factor Analysis………………………………….…..33
5 Descriptive Analysis……………………………………………. 34
6 Correlation Analysis……………………………………………..36
7 Regression Analysis (Without Impact of Moderator)…………...37
8 Regression Analysis (With Impact of Moderator)………………38
List of figure
S. NO. Page No.
1 Theoretical Framework………………………………………………..21
Barriers to Implementation of Green Human Resource Management Practices
Ammaria Kanwal, Maaz Ayub, Shaiza Nazir and Muhammad Abid Awan
Department of Gift Business School
Abstract
The purpose of this...

...LC•GC Europe Online Supplement
statistics and dataanalysis
9
Analysis of Variance
Shaun Burke, RHM Technology Ltd, High Wycombe, Buckinghamshire, UK. Statistical methods can be powerful tools for unlocking the information contained in analytical data. This second part in our statistics refresher series looks at one of the most frequently used of these tools: Analysis of Variance (ANOVA). In the previous paper we examined the initial steps in describing the structure of the data and explained a number of alternative significance tests (1). In particular, we showed that t-tests can be used to compare the results from two analytical methods or chemical processes. In this article, we will expand on the theme of significance testing by showing how ANOVA can be used to compare the results from more than two sets of data at the same time, and how it is particularly useful in analysing data from designed experiments.
With the advent of built-in spreadsheet functions and affordable dedicated statistical software packages, Analysis of Variance (ANOVA) has become relatively simple to carry out. This article will therefore concentrate on how to select the correct variant of the ANOVA method, the advantages of ANOVA, how to interpret the results and how to avoid some of the pitfalls. For those wanting more...

...tasks:
Data Collection:
• Determine 4 to 6 variables (at least 2 quantitative and 2 qualitative) you would like to collect information on from the sample.
• Write a survey that asks clear questions that will allow you to collect your data. Type this survey up in (with your name somewhere at the top) and print 45 copies.
Research Questions:
• Write at least 3 research questions about the population that can be answered from your data. Two or more of these questions should be able to be answered by a hypothesis test (these questions will investigate relationships between variables) and one or more could be answered from a confidence interval (this question will investigate the true value of an unknown parameter).
DataAnalysis:
Conduct appropriate dataanalysis techniques to answer your research questions. This analysis should include two or more hypothesis tests, can include one confidence interval, and should include at least one graph.
(If you don’t do a confidence interval, you should do at least 3 hypothesis tests.)
Paper:
Write a paper that includes the following:
• An introduction that gives an overview of the big idea of your project and the research questions you sought to answer
• A methods section that clearly states your methodology (what data did you collect, how did you collect it, and how do you...

...Statistical Techniques for Handling Missing Data Dr. John M. Cavendish
4 Part a1 Data were collected from 430 undergraduate college students for the purpose of examining the relationship between student personality characteristics and their preference for personality styles in their lecturers. Table 1 below presents a summary of the data collected. Of the 430 subjects for whom data was attempted, with 5 subjects providing nodata, Of the 425 subjects included in dataanalysis, 307 were female, 117 were male, and 1 failed to indicate their gender. With the exception of Age and Student wants Extroversion in lecturers, the Coefficients of Skewness and Kurtosis are within normal limits. In the instance of Age, the lower outliers are obviously mistakes, since it would be impossible to have students with age 0 and 2 years old in the study. However, even when they are eliminated, this variable does not approach normality. It is also apparent from Table 1 that all variables have missing values. While most have less than 5% of the values missing, the Student wants Extroversion in lecture variable has 147 (34%) of its values missing.
Table 1 Summary of Lecture Preference Study Data N Statistic lecturE Age studentN studentE studentO studentA studentC lectureN lecturO lecturA lecturC Valid N (listwise) 283 404 420 418 418 413 416 417 420 417 417 265 Statistic 12.96...

...•€€€€€€€€€How sections constituting this chapter?
3.2 Unit of analysis & sampling strategy
•€€€€€€€€€Who was your target sample or respondents and why?
•€€€€€€€€€How did you sample or recruit the respondents? Probability versus non-probability sampling?
•€€€€€€€€€How many people did you recruit and why?
•€€€€€€€€€Refer to journal articles to understand how to decide a sampling strategy.
3.3 Research design
•€€€€€€€€€Which research method did you use and why? Qualitative versus quantitative?
•€€€€€€€€€Please note that students often provide textbook-based rationale in this chapter (e.g. it’s quick and cheap and easy to administer).
•€€€€€€€€€Be very specific with your rationale, try to link to your research objectives and the theoretical or managerial outcomes that you wish to achieve.
3.4 Questionnaire design and administration (OR 3.4 Interviewing Process and Protocol)
•€€€€€€€€€The section title will vary depending on whether you opted for a quantitative or qualitative method.
•€€€€€€€€€If you’re doing a QUALITATIVE research, this section should be Interviewing Process and Protocol.
•€€€€€€€€€You need to specify how many sections you will have in the questionnaire, what purpose of each section, and how many questions in each section.
•€€€€€€€€€Questionnaire administration is about the process (e.g. online versus offline versus face-to-face) that you have applied in collecting questionnaire...

...Introduction | | |AJ DAVIS is a department store chain, which has many credit customers and wants to find out more information about these customers. A sample of 50 credit customers is selected with data collected on the following five variables:
1. LOCATION (Rural, Urban, Suburban)
2. INCOME (in $1,000's – be careful with this)
3. SIZE (Household Size, meaning number of people living in the household)
4. YEARS (the number of years that the customer has lived in the current location)
5. CREDIT BALANCE (the customers current credit card balance on the store's credit card, in $).
|PROJECT PART A: Exploratory DataAnalysis | |
• Open the file MATH533 Sept 2013 Project Consumer.xls from the Course Project Data Set folder in Doc Sharing.
• Students MUST download and use the data file currently posted inside DocSharing. This data set changes each session and IS NOT the same used in prior sessions.
• For each of the five variables, process, organize, present and summarize the data. Analyze each variable by itself using graphical and numerical techniques of summarization. Use MINITAB as much as possible, explaining what the printout tells you. You may wish to use some of the following graphs: stem-leaf diagram, frequency/relative frequency table,...

...15 Methods of DataAnalysis in Qualitative Research
Compiled by Donald Ratcliff
1. Typology - a classification system, taken from patterns, themes, or other kinds of groups of data. (Patton pp. 393,398) John Lofland & Lyn Lofland Ideally, categories should be mutually exclusive and exhaustive if possible, often they aren't. Basically a list of categories. example: Lofland and Lofland's 1st edition list: acts, activities, meanings, participation, relationships, settings (in the third edition they have ten units interfaced by three aspects--see page 114--and each cell in this matrix might be related to one of seven topics--see chapter seven).
2. Taxonomy (See Domain Analysis - often used together, especially developing taxonomy from a single domain.) James Spradley A sophisticated typology with multiple levels of concepts. Higher levels are inclusive of lower levels. Superordinate and subordinate categories
3. Constant Comparison/Grounded Theory (widely used, developed in late 60's) Anselm Strauss
• • • • •
• • •
Look at document, such as field notes Look for indicators of categories in events and behavior - name them and code them on document Compare codes to find consistencies and differences Consistencies between codes (similar meanings or pointing to a basic idea) reveals categories. So need to categorize specific events We used to cut apart copies of field notes, now use computers....