MPC 005 Solved Assignment 2022-23

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Course Code: MPC-005

Assignment Code: MPC-001/ASST/TMA/2022-23

Marks: 100

NOTE: All questions are compulsory

Section A

Answer the following question in about 1000 words each. 15x3=45Marks

1. Explain the factorial design with the help of a suitable example.

Experimental Design

Jessie is interested in studying whether or not girls will do better than boys on a history test. She also wonders if it will matter if the test is hard or easy. In other words, will girls do better than boys on both hard and easy tests?

The first step for Jessie or any researcher to take when trying to answer an experimental question is to engage in experimental design, or the process of choosing how to run an experiment to answer the research question of interest.

In order to figure out her experimental design, Jessie has to identify her variables, or measures that change. There are two main types of variables: independent variables, which are also sometimes called factors, are variables whose values do not depend on the value of another variable; and dependent variables are variables whose values depend on the independent variables.

Jessie has two independent variables, gender and difficulty of test, and one dependent variable, performance on the test. We know that gender and difficulty are independent variables because they are not caused by any of the other variables in the study. The subjects' gender does not change because they are given a harder test or because they did well on a test.

But performance on the test does change (or so Jessie assumes) based on the independent variables. If Jessie's hypothesis is correct, a subject will do better on the test if she is a girl.

Factorial Design

Many studies ask the question: 'How does this one independent variable affect this one dependent variable?' For example, perhaps Jessie just wants to know how gender affects how subjects do on a test. That's a basic experimental design.

But much of research is concerned with more than one independent variable. For example, Jessie wants to know if gender and difficulty of test affect performance on the test. Her question is, essentially: 'How do these two independent variables affect this one dependent variable?'

Remember that independent variables are sometimes called factors. When you have multiple independent variables in a single study, it is called factorial design.

A factorial design does not have to have just two independent variables; it can have as many as you want. What if Jessie decides that, besides gender and difficulty of test, the time of day when the test is taken also affects how subjects do? Now she has three independent variables to look at: gender, difficulty, and time of day.

One thing that's different in factorial designs from simpler designs is that we have to look at how each independent variable affects the dependent variable, but also how the combination of the independent variables affect the dependent variable.

Let's go back to Jessie's simplest experiment for a moment: she wants to know how gender affects test performance. In that study, all she has to look at is how that one independent variable (gender) affects her dependent variable (test performance).

But when Jessie adds in an independent variable like difficulty of the test, suddenly she has many different things to look at. She has to look at how gender affects test performance and how difficulty affects test performance. But she also has to look at how gender and difficulty together affect test performance.

In the simplest psychology experiments, researchers look at how one independent variable affects one dependent variable. But what happens if researchers want to look at the effects of multiple independent variables? This type of study that involve the manipulation of two or more variables is known as a factorial design.

As you may recall, the independent variable is the variable of interest that the experimenter will manipulate. The dependent variable, on the other hand, is the variable that the researcher then measures. By doing this, psychologists can see if making changes to the independent variable results in some type of change in the dependent variable.

For example, imagine that a researcher named Sarah wants to do an experiment looking at whether sleep deprivation has a negative impact on reaction times during a driving test. If she were to only perform the experiment using these variables – the sleep deprivation being the independent variable and the performance on the driving test being the dependent variable – it would be an example of a simple experiment.

However, let’s imagine that Sarah is also interested in learning if sleep deprivation impacts the driving abilities of men and women differently. She has just added a second independent variable of interest (sex of the driver) into her study, which now makes it a factorial design.

One common type of experiment is known as a 2×2 factorial design. In this type of study, there are two factors (or independent variables) and each factor has two levels. The number of digits tells you how many in independent variables (IVs) there are in an experiment while the value of each number tells you how many levels there are for each independent variable. So, for example, a 4×3 factorial design would involve two independent variables with four levels for one IV and three levels for the other IV.

One of the big advantages of factorial designs is that they allow researchers to look for interactions between independent variables. An interaction is a result in which the effects of one experimental manipulation depends upon the experimental manipulation of another independent variable.

For example, imagine that researchers want to test the effects of a memory-enhancing drug. Participants are given one of three different drug doses, and then asked to either complete a simple or complex memory task. The researchers note that the effects of the memory drug are more pronounced with the simple memory tasks, but not as apparent when it comes to the complex tasks. In this 3×2 factorial design, there is an interaction effect between the drug dosage and the complexity of the memory task.

So if researchers are manipulating two or more independent variables, how exactly do they know which effects are linked to which variables?

“It is true that when two manipulations are operating simultaneously, it is impossible to disentangle their effects completely,” explain authors Breckler, Olson, and Wiggins in their book Social Psychology Alive. “Nevertheless, the researchers can explore the effects of each independent variable separately by averaging across all levels of the other independent variable. This procedure is called looking at the main effect.”

Examples of Factorial Designs

A university wants to assess the starting salaries of their MBA graduates. The study looks at graduates working in four different employment areas: accounting, management, finance, and marketing. In addition to looking at the employment sector, the researchers also look at gender. In this example, the employment sector and gender of the graduates are the independent variables, and the starting salaries are the dependent variables. This would be considered a 4×2 factorial design.

Researchers want to determine how the amount of sleep a person gets the night before an exam impacts performance on a math test the next day. But the experimenters also know that many people like to have a cup of coffee (or two) in the morning to help them get going. So, the researchers decide to look at how the amount of sleep and the amount of caffeine influence test performance. The researchers then decide to look at three levels of sleep (4 hours, 6 hours, and 8 hours) and only two levels of caffeine consumption (2 cups versus no coffee). In this case, the study is a 3×2 factorial design.

2. Explain the assumptions, theories and steps of discourse analysis.

3. What are the different steps followed for conducting a scientific research?

Section B

Answer the following questions in about 400 words each. 5x5=25Marks

4. Type of Quasi Experimental Designs.

5. Research Biases.

6. Distinguish between field and experimental research design.

7. Types of questions that can be used in a survey research.

8. Strategies of interpreting data in a qualitative research.

Section C

Answer the following in about 50 words each. 10x3=30Marks

9. Difference between causal comparative and experimental research design

10. Definition of research design.

11. Significance of hypothesis formulation.

12. Meaning of reliability.

13. Method of snow ball sampling.

14. Difference between independent and dependent variable.

15. Relevance of grounded theory.

16. Meaning of ethnography.

17. Criteria for selecting a case study.

18. Concept of cross sectional survey research design

MPC 005 Handwritten Assignment 2022-23

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Important Note - You may be aware9 that you need to submit your assignments before you can appear for the Term End Exams. Please remember to keep a copy of your completed assignment, just in case the one you submitted is lost in transit.

Submission Date :

· 31st March 2023 (if enrolled in the July 2022-23 Session)

· 30th Sept, 2023 (if enrolled in the January 2023 session).

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MPC 005 RESEARCH METHODS Assignment 2022-23 Before attempting the assignment, please read the following instructions carefully.

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MPC 005 Solved Assignment 2022-23 You will find it useful to keep the following points in mind:

1. Planning: Read the questions carefully. Go through the units on which they are based. Make some points regarding each question and then rearrange these in a RESEARCH METHODSal order. And please write the answers in your own words. Do not reproduce passages from the units.

2. Organisation: Be a little more selective and analytic before drawing up a rough outline of your answer. In an essay-type question, give adequate attention to your introduction and conclusion. The introduction must offer your brief interpretation of the question and how you propose to develop it. The conclusion must summarise your response to the question. In the course of your answer, you may like to make references to other texts or critics as this will add some depth to your analysis.

3. Presentation: Once you are satisfied with your answers, you can write down the final version for submission, writing each answer neatly and underlining the points you wish to emphasize.

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MPC 005 Solved Assignment 2022-23

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