BRM 203 unit 5 Data Analysis Dr Kanchan.pptx

Study Material for Management Students

1. BUSINESS RESEARCH METHODS UNIT 5 DATA ANALYSIS Dr. KANCHAN KUMARI FACULTY OF MANAGEMENT AND INTERNATIONAL BUSINESS

2. Editing Data editing is the application of checks to detect missing, invalid or inconsistent entries or to point to data records that are potentially in error . No matter what type of data you are working with, certain edits are performed at different stages or phases of data collection and processing. It is pre-requisite for accuracy . It is useful in the elimination of the incorrect reply. It ensures the consistency of the data collected and avoids contradictions.

3. Coding Coding is a qualitative data analysis strategy in which some aspect of the data is assigned a descriptive label that allows the researcher to identify related content across the data . HOW TO USE: Choose whether you'll use deductive or inductive coding. Read through your data to get a sense of what it looks like. ... Go through your data line-by-line to code as much as possible. ... Categorize your codes and figure out how they fit into your coding frame.

4. Tabular representation of data One of the simplest methods used to analyze the data and to display the data is in tabular form. In the tabular form, you get a systematic arrangement of rows and columns. The first column is used to indicate the titles and the first row is also used to indicate the same . Data can be represented in tabular form showing the frequnecy of each distribution. This representation in tabular form is called frequency distribution table . Makes representation of data easy . Makes it easy to analyze the data. Makes it easy to compare data. The data is represented in a readable manner which saves space and the reader's time.

5. Frequency T ables Frequency means the number of times a value appears in the data . A table can quickly show us how many times each value appears. If the data has many different values, it is easier to use intervals of values to present them in a table. Example- is the age of the 934 Nobel Prize winners up until the year 2020. Frequency Analysis is a part of descriptive statistics . In statistics, frequency is the number of times an event occurs. Frequency Analysis is an important area of statistics that deals with the number of occurrences (frequency) and analyzes measures of central tendency, dispersion, percentiles, etc.

6. Construction of frequency distributions To construct a frequency distribution, first, note the specific classes determined by intervals in one column, then sum the numbers in each isolated category based on how many times it shows up. The frequency can then be noted in the second column. We construct of frequency by Calculating the range of the data set. Next, divide the range by the number of the group you want your data in and then round up. After that, use class width to create groups. Finally, find the frequency for each group.

7. Graphical Representation of Data: Graphical representation refers to the use of charts and graphs to visually analyze and display, interpret numerical value, clarify the qualitative structures . The data is represented by a variety of symbols such as line charts, bars, circles, ratios. A chart is a graphical representation of data, in which "the data is represented by symbols, such as bars in a bar chart, lines in a line chart, or slices in a pie chart". A chart can represent tabular numeric data, functions or some kinds of qualitative structure and provides different info. Bar graphs ,Histograms , Frequency polygons are all graphical representation of data.

8. Appropriate Usage of Bar charts, Bar charts should be used when you are showing segments of information. Vertical bar charts are useful to compare different categorical or discrete variables , such as age groups, classes, schools, etc., as long as there are not too many categories to compare. They are also very useful for time series data. It allows you to compare different sets of data among different groups easily . It instantly demonstrates this relationship using two axes, where the categories are on one axis and the various values are on the other. A bar graph can also illustrate important changes in data throughout a period of time.

9. Pie charts A pie chart (or a circle chart) is a circular statistical graphic which is divided into slices to illustrate numerical proportion . In a pie chart, the arc length of each slice (and consequently its central angle and area) is proportional to the quantity it represents. In short, a pie chart can only be used if the sum of the individual parts add up to a meaningful whole, and is built for visualizing how each part contributes to that whole . Meanwhile, a bar chart can be used for a broader range of data types, not just for breaking down a whole into components

10. Histogram A histogram is a statistical graph that represents the distribution of a continuous dataset through plotted bars, each representing a particular category or class interval . The bar height reflects the frequency or count of data points within each group. It is often used to illustrate the major features of the distribution of the data in a convenient form . It is also useful when dealing with large data sets (greater than 100 observations). It can help detect any unusual observations of any gaps in the data.

11. Hypothesis: A hypothesis is a concept or idea that you test through research and experiments . In other words, it is a prediction that is can be tested by research. Most researchers come up with a hypothesis statement at the beginning of the study. A hypothesis is an assumption, an idea that is proposed for the sake of argument so that it can be tested to see if it might be true. Research hypothesis is a statement that introduces a research question and proposes an expected result . It is an integral part of the scientific method that forms the basis of scientific experiments. Therefore, you need to be careful and thorough when building your research hypothesis. Example- It's essentially an educated guess—based on observations—of what the results of your experiment or research will be. Some hypothesis examples include: If I water plants daily they will grow faster . Adults can more accurately guess the temperature than children can. Butterflies prefer white flowers to orange ones.

12. Qualities of a good Hypothesis Testability : A hypothesis should be testable and should not be a moral judgment. It should be possible to collect empirical evidence to test techniques. A good research hypothesis should have a sufficient literature background. The formulation of research hypothesis . Hypotheses bring clarity, specificity and focus to a research problem. Hypotheses primarily arise from a set of hunches that are tested through a study The hypothesis should be mentioned in clear and precise statements which should have scoper for conducting more tests. Define the variables . Independent variables are the ones that are manipulated, controlled, or changed. Independent Falsifiability : A hypothesis should be capable of being proven false. This means that there must be a conceivable observation or experiment that could . If the hypothesis is relational , it should state the relationship between variables. · Observations from the past studies, present-day experiences. Consistency : Hypothesis should be logically consistent. The propositions derived should not be contradictory. Objectivity:

13. Framing Null Hypothesis & Alternative Hypothesis To write a null hypothesis, first start by asking a question. Rephrase that question in a form that assumes no relationship between the variables . It assume a treatment has no effect. Write your hypothesis in a way that reflects this. The null hypothesis is the statement or claim being made (which we are trying to disprove) and the alternative hypothesis is the hypothesis that we are trying to prove and which is accepted if we have sufficient evidence to reject the null hypothesis . The formula for the Null hypothesis is H0:p=po and the formula for test static is Z=P−Po√P−P0N. Here, p0 is the null hypothesis, and p is the sample proportion.

14. Concept of Hypothesis Testing The purpose of hypothesis testing is to test whether the null hypothesis (there is no difference, no effect) can be rejected or approved . If the null hypothesis is rejected, then the research hypothesis can be accepted. If the null hypothesis is accepted, then the research hypothesis is rejected. A hypothesis is an assumption, an idea that is proposed for the sake of argument so that it can be tested to see if it might be true . In the scientific method, the hypothesis is constructed before any applicable research has been done, apart from a basic background review

15. Importance of Hypothesis Testing Research hypothesis is important as it provides a direction for the research, establishes relationships between variables, and helps in testing and verifying predictions . The research hypothesis is important because it helps guide the research process and provides a framework for testing and analyzing data

16. Analysis of Variance Analysis of variance (ANOVA) is a statistical technique used to check if the means of two or more groups are significantly different from each other . ANOVA checks the impact of one or more factors by comparing the means of different samples ANOVA, or Analysis of Variance, is a test used to determine differences between research results from three or more unrelated samples or groups.

17. One way and two way Classifications Such an experimental layout is commonly known as one-way classification in which sample observations are classified (grouped) by only a single criterion . It provides the simplest data structure containing one or more observations at every level of a single factor. Some times you have more than one categorical predictor variables at a different levels and a continuous response variable then it is called two-way classification. Two-way classified data can be treated in three ways 1. Analysis of two-way classified data with one observation per cell.

18. Mechanism of Report Writing- A detailed presentation of the findings of the study, with supporting data in the form of tables and charts together with a validation of results , is the next step in writing the main text of the report. This generally comprises the main body of the report extending over several chapters. 1 Choose a topic based on the assignment. Before you start writing, you need to pick the topic of your report. ... 2 Conduct research. ... 3 Write a thesis statement. ... 4 Prepare an outline. ... 5 Write a rough draft. ... 6 Revise and edit your report. ... 7 Proofread and check for mistakes.

19. P reliminary section, main report, PRELIMINARY PARTS The preliminary parts of a report consist of the cover, title page, copyright notice, acknowledgements, authorization letter, table of contents, list of illustrations, and synopsis or executive summary . In certain cases, the synopsis is called abstract. It should include your name and course; the title of the assignment and any references; the lecturer it is for etc . Check with your department for clear information. A report should also normally include an abstract and a contents page.

20. I nterpretation of results The interpretation of your results is the section where you explain the meaning and implications of your findings in relation to your research objectives, questions, and hypotheses . It is also where you discuss how your results fit with the existing literature, theory, and practice in your field. "Interpretation refers to the process of making sense of numerical data that has been collected, analysed and presented ". The interpretation of results should include a discussion of the evidence gathered . This includes aspects of validity, strengths and weaknesses of the evidence, possible sources of bias that may be present in the included studies, and the potential bias of the review.

21. S uggestions and recommendations When you suggest something, you offer it as a possibility or an alternative. It is often used in casual conversations or when offering a tentative or informal idea. 'Recommend', on the other hand, involves advocating a particular item or course of action based on expertise, experience, or careful consideration. Example- Radha suggested watching a movie tonight . Based on your symptoms, I recommend that you take this medication for relief. I would recommend starting with the beginner's level before progressing to advanced yoga poses. I would suggest starting with the beginner's level before progressing to advanced yoga poses.

22. L imitations of the study. Study limitations are the constraints placed on the ability to generalize from the results, to further describe applications to practice, and/or related to the utility of findings that are the result of the ways in which you initially chose to design the study or the method used to establish internal and external ... This means that researchers have to define what the study is focusing on. Similarly, they have to define what the study is not going to cover (these often comprise the limitations of the study). The scope is always decided in the preliminary stages of a study.

23. Report formulation A research report is a well-crafted document that outlines the processes, data, and findings of a systematic investigation . It is an important document that serves as a first-hand account of the research process, and it is typically considered as an objective and accurate source of information.

24. 7 steps of Report Writing Choose a topic based on the assignment. 2 Conduct research. 3 Write a thesis statement. 4 Prepare an outline. 5 Write a rough draft. 6 Revise and edit your report. 7 Proofread and check for mistakes.

25. THANK YOU Dr. Kanchan Kumari