IGNOU BPCC 108 Solved Assignment 2022-23

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Important Note – IGNOU BPCC 108 Solved Assignment 2022-2023 Download Free You may be aware 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.

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Submission Date :

31st March 2033 (if enrolled in the July 2033 Session)
30th Sept, 2033 (if enrolled in the January 2033 session).

All questions are compulsory.

Answer the following descriptive category questions in about 500 words each. Each question carries 20 marks in Assignment one.

Answer the following short category questions in about 100 words each. Each question carries 5 marks in Assignment two.

Assignment One

1. Describe the assumptions of parametric and non-parametric statistics.
The Four Assumptions of Parametric Tests

In statistics, parametric tests are tests that make assumptions about the underlying distribution of data.Common parametric tests include:

One sample t-test
Two sample t-test
One-way ANOVA

In order for the results of parametric tests to be valid, the following four assumptions should be met:1. Normality – Data in each group should be normally distributed.2. Equal Variance – Data in each group should have approximately equal variance.3. Independence – Data in each group should be randomly and independently sampled from the population.4. No Outliers – There should be no extreme outliers.This tutorial provides a brief explanation of each assumption along with how to check if each assumption is met.Assumption 1: NormalityParametric tests assume that each group is roughly normally distributed.

If the sample sizes of each group are small (n < 30), then we can use a Shapiro-Wilk test to determine if each sample size is normally distributed.If the p-value of the test is less than a certain significance level, then the data is likely not normally distributed.However, if the sample sizes are large then it’s better to use a Q-Q plot to visually check if the data is normally distributed.
If the data points roughly fall along a straight diagonal line in a Q-Q plot, then the dataset likely follows a normal distribution.Assumption 2: Equal VarianceParametric tests assume that the variance of each group is roughly equal.We can visually check if this assumption is met by creating side-by-side boxplots for each group to see if the boxplots of each group are roughly the same size.Another way to check if this assumption is met is to use the following rule of thumb: If the ratio of the largest variance to the smallest variance is less than 4, then we can assume the variances are approximately equal and use the two sample t-test.

For example, suppose group 1 has a variance of 24.5 and group 2 has a variance of 15.2. The ratio of the larger sample variance to the smaller sample variance would be calculated as:Ratio: 24.5 / 15.2 = 1.61Since this ratio is less than 4, we could assume that the variances between the groups are approximately equal.Assumption 3: IndependenceParametric tests assume that the observations in each group are independent of observations in every other group.The easiest way to check this assumption is to verify that the data was collected using a probability sampling method – a method in which every member in a population has an equal probability of being selected to be in the sample.

Examples of probability sampling methods include:

Simple random sampling
Stratified random sampling
Cluster random sampling
Systematic random sampling

If one of these methods was used to collect the data, we can assume that this assumption is met.

Assumption 4: No Outliers

Parametric tests assume that there are no extreme outliers in any group that could adversely affect the results of the test. One way to visually check for outliers is to create boxplots for each group to see if there are any clear outliers that are much larger than the rest of the other observations in the group. Another way to detect outliers is to perform Grubbs’ Test, which is a formal statistical test that can be used to identify outliers.

2. Compute One Way ANOVA for the following data:

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Assignment Two

3.Elucidate factorial designs with the help of suitable examples.

4. Explain the fundamental concepts in determining the significance of the difference between means.

5. Compute Chi-square for the following data:

6. Compute Mann Whitney U for the following data :

7. Explain the procedure for computation of correlation using Microsoft Excel.

8. Explain, data view, variable view and output view of SPSS.

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IGNOU BPCC 108 Solved Assignment 2022-2023 Download Free Before attempting the assignment, please read the following instructions carefully.

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IGNOU BPCC 108 Solved Assignment 2022-23 You will find it useful to keep the following points in mind:

Planning: Read the questions carefully. IGNOU BPCC 108 Assignment 2022-23 Download Free Download PDF Go through the units on which they are based. Make some points regarding each question and then rearrange these in a logical order. And please write the answers in your own words. Do not reproduce passages from the units.
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. IGNOU BPCC 108 Solved Assignment 2022-2023 Download Free Download PDF 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.
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BPCC 108 Handwritten Assignment 2022-23

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IGNOU BPCC 108 Solved Assignment 2022-23