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IOP2601 Assignment 4 (Detailed Answers & Solutions) Semester 2 2023 (Due 10 October 2023) RRLLB81 - LLB Research Report (IOP2601)

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Complete IOP2601 Assignment 4 Answers- Semester 2-2023. Distinction Guaranteed or money back! This document includes detailed answers, guidelines and calculations for the IOP2601 Assessment 4 due 10 October 2023. TRUSTED & QUALITY SOLUTIONS. Distinction Guaranteed. Feel Free to DM for any further assistance. QUESTION 1 (a) The summary report includes both descriptive and inferential statistics. Distinguish between these two categories of statistical methods and techniques. Provide examples.

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2023




IOP2601 Assessment 04 Complete Answers

Due: Tuesday 10 October 2023 @ 23:00

Semester 2/ 2023

Organisational Research Methodology

Weighs 40% of Course mark 

Unique Number: 387303

, QUESTION ANSWERS
NUMBER
QUESTION 1
(a) Descriptive statistics – a technique for organising, summarising and describing data. This
is the descriptive research approach. Descriptive statistics include the mean, variance,
skewedness and kurtosis.


Inferential statistics – a technique applied to samples in order to make inferences about
populations. This is also known as the experimental research approach. Inferential statics
include the linear regression analysis, analysis of variance (ANOVA), logit/Probit models
and null hypothesis testing.
P.G. 10 Study Guide


(b) Negatively skewed distribution (skewed to the left, which means the long tail points
towards the negative or small numbers). For example, students’ exam scores make a curve
that is skewed to the left means that most students have high performance scores and a
small number of students would have low performance scores, these are the outliners in the
data set that causes it to be negatively skewed.


Positively skewed distribution (skewed to the right, which means the long tail points
towards the positive or large numbers). For example, students’ exam scores make a curve
that is skewed to the right means that most students have low performance scores and a
small number of students that have high performance scores, these are the outliners in the
data set that causes it to be positively skewed.
P.G. 39 Study Guide, P.G. 28 Textbook




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