2025

Explain scales of measurement and discuss assumption of parametric statistics.

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Explain Scales of Measurement and Discuss Assumption of Parametric Statistics Introduction In psychological research and statistics, how data is measured determines the type of analysis that can be conducted. The concept of scales of measurement is foundational in selecting appropriate statistical techniques. Furthermore, parametric statistical methods, which are widely used in psychology, rest on certain […]

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Discuss divergence in normality with the help of suitable diagram and describe the factors causing divergence in the normal distribution. Discuss how divergence in normality is measured.

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Divergence in Normality: Meaning, Diagrams, Causes, and Measurement Introduction In the field of statistics, particularly in psychological research, the concept of normal distribution holds significant importance. Many statistical methods, including parametric tests, assume that the data follows a normal distribution. However, in real-world data, this assumption is not always met. When data deviates from the

Discuss divergence in normality with the help of suitable diagram and describe the factors causing divergence in the normal distribution. Discuss how divergence in normality is measured. Read More »

Compute ANOVA (parametric statistics) for the following data: that indicates the scores obtained by three group on employees on emotional intelligence scale:

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Compute ANOVA (Parametric Statistics) for the Given Data on Emotional Intelligence Introduction Analysis of Variance (ANOVA) is a powerful statistical technique used to determine whether there are any statistically significant differences between the means of three or more independent groups. In this case, we are given emotional intelligence scores of employees categorized into three groups:

Compute ANOVA (parametric statistics) for the following data: that indicates the scores obtained by three group on employees on emotional intelligence scale: Read More »

Explain the meaning of descriptive statistics and describe organization of data.

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Explain the Meaning of Descriptive Statistics and Describe Organization of Data Introduction Statistics plays a crucial role in the field of psychology by helping researchers and professionals make sense of data. Descriptive statistics, in particular, are foundational tools used to summarize, organize, and interpret raw data in a meaningful way. Without statistical analysis, it would

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MPC-005 Assignment Answer Index (2024-25)

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IGNOU MPC-005: Research MethodsTutor Marked Assignment (TMA) 2024–25 Course Code: MPC-005 Assignment Code: MPC-005/ASST/TMA/2024-25 Total Marks: 100 Note: All questions are compulsory. SECTION – AAnswer the following questions in 1000 words each. (3 x 15 = 45 marks) Define sampling. Discuss the different methods of sampling – Read Answer Discuss the types, advantages, limitations and

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Memory effect

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Memory Effect Memory effect refers to the influence of prior exposure on a participant’s responses in a study. In repeated measures or longitudinal designs, participants may remember previous questions or answers, which can affect the accuracy of current responses and introduce bias. It threatens internal validity.

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Research biases

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Research Biases Research biases are systematic errors that affect the validity and reliability of study results. Common types include: Selection bias: Unequal group characteristics Confirmation bias: Researcher favors data supporting their hypothesis Measurement bias: Faulty instruments or procedures skew data Publication bias: Preference for publishing positive results over null findings

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Objectivity Safeguards

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Objectivity Safeguards Objectivity safeguards are methods researchers use to minimize bias and ensure neutrality in data collection and analysis. Common safeguards include: Standardized procedures: Using the same protocols for all participants Blinding: Participants or researchers are unaware of group assignments Replication: Repeating studies to confirm findings Peer review: External evaluation of research methods and results

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Causal Comparative research design

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Causal Comparative Research Design Causal comparative research design, also known as ex post facto design, involves comparing two or more groups based on a pre-existing condition or characteristic to determine cause-effect relationships. The independent variable is not manipulated but observed as it naturally exists. Example: Comparing academic performance of students from rural and urban schools

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