BPC-004 Solved Assignment 2023-2024

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BPC-004 Solved Assignment 2023-2024 Sample Solution
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bpc-004-solved-assignment-2023-2024—-8e24e610-06c9-4b43-84f6-a5bf6ef5ab5c

bpc-004-solved-assignment-2023-2024—-8e24e610-06c9-4b43-84f6-a5bf6ef5ab5c

BPC-004 Solved Assignment 2023-2024
  1. Explain the two types of inferential procedures. Describe the general procedure for testing a hypothesis.
Answer:
Two Types of Inferential Procedures
Inferential statistics involve making inferences about a population based on information obtained from a sample. There are two main types of inferential procedures:
  1. Estimation: This procedure involves estimating a population parameter (such as the mean or proportion) based on a sample statistic. There are two types of estimation:
    • Point Estimation: Provides a single value as an estimate of the population parameter. For example, using the sample mean as an estimate of the population mean.
    • Interval Estimation: Provides a range of values (an interval) that is likely to contain the population parameter. This is often expressed as a confidence interval, such as a 95% confidence interval for the population mean.
  2. Hypothesis Testing: This procedure involves testing a claim or hypothesis about a population parameter. It is a formal method for testing whether a hypothesis about a parameter is likely to be true, based on sample data. There are various types of hypothesis tests, depending on the parameter being tested and the nature of the data.
General Procedure for Testing a Hypothesis
The general procedure for testing a hypothesis typically involves the following steps:
  1. Formulate the Hypotheses:
    • Null Hypothesis (H0): This is a statement of no effect or no difference. It is the hypothesis that is initially assumed to be true.
    • Alternative Hypothesis (Ha or H1): This is the hypothesis that represents the claim or effect we wish to test. It is considered to be true if the null hypothesis is rejected.
  2. Select a Significance Level (α): This is the probability of rejecting the null hypothesis when it is actually true (Type I error). Common significance levels are 0.05, 0.01, and 0.10.
  3. Choose the Appropriate Test Statistic: The test statistic is a numerical value that is calculated from the sample data and is used to make a decision about the null hypothesis. The choice of test statistic depends on the type of data and the hypothesis being tested.
  4. Determine the Rejection Region: Based on the significance level and the test statistic’s distribution, determine the critical value(s) that define the rejection region. If the calculated test statistic falls into this region, the null hypothesis will be rejected.
  5. Calculate the Test Statistic: Using the sample data, calculate the value of the test statistic.
  6. Make a Decision: Compare the calculated test statistic to the critical value(s) to determine whether to reject or fail to reject the null hypothesis.
    • If the test statistic falls into the rejection region, reject the null hypothesis in favor of the alternative hypothesis.
    • If the test statistic does not fall into the rejection region, fail to reject the null hypothesis.
  7. Draw a Conclusion: Based on the decision, draw a conclusion about the hypothesis in the context of the problem.
This general procedure can be adapted and modified based on the specific type of hypothesis test being conducted and the characteristics of the data.
  1. Emotional Intelligence Scale and Occupational Stress Scale were administered to a group of employees. The scores obtained are given below. Calculate Pearson’s Product Moment Correlation for the following data:
A B C D E F G H I J
Scores on Emotional
Intelligence Scale
Scores on Emotional Intelligence Scale| Scores on Emotional | | :— | | Intelligence Scale |
 5 4 3 4 3 2 5 6 4 3
Scores on Occupational
Stress Scale
Scores on Occupational Stress Scale| Scores on Occupational | | :— | | Stress Scale |
 6 9 8 7 2 3 3 6 4 5
A B C D E F G H I J “Scores on Emotional Intelligence Scale” 5 4 3 4 3 2 5 6 4 3 “Scores on Occupational Stress Scale” 6 9 8 7 2 3 3 6 4 5| | A | B | C | D | E | F | G | H | I | J | | :— | :—: | :—: | :—: | :—: | :—: | :—: | :—: | :—: | :—: | :—: | | Scores on Emotional <br> Intelligence Scale | 5 | 4 | 3 | 4 | 3 | 2 | 5 | 6 | 4 | 3 | | Scores on Occupational <br> Stress Scale | 6 | 9 | 8 | 7 | 2 | 3 | 3 | 6 | 4 | 5 |
Answer:
original image
Correlation Coefficient r r r\mathrm{r}r :
r = n ⋅ ∑ x y − ∑ x ⋅ ∑ y n ⋅ ∑ x 2 − ( ∑ x ) 2 ⋅ n ⋅ ∑ y 2 − ( ∑ y ) 2 r = n ⋅ ∑ x y − ∑ x ⋅ ∑ y n ⋅ ∑ x 2 − ∑ x 2 ⋅ n ⋅ ∑ y 2 − ∑ y 2 r=(n*sum xy-sum x*sum y)/(sqrt(n*sumx^(2)-(sum x)^(2))*sqrt(n*sumy^(2)-(sum y)^(2)))r=\frac{n \cdot \sum x y-\sum x \cdot \sum y}{\sqrt{n \cdot \sum x^2-\left(\sum x\right)^2} \cdot \sqrt{n \cdot \sum y^2-\left(\sum y\right)^2}}r=n⋅∑xy−∑x⋅∑yn⋅∑x2−(∑x)2⋅n⋅∑y2−(∑y)2
= 10 ⋅ 212 − 39 ⋅ 53 10 ⋅ 165 − ( 39 ) 2 ⋅ 10 ⋅ 329 − ( 53 ) 2 = 2120 − 2067 1650 − 1521 ⋅ 3290 − 2809 = 53 129 ⋅ 481 = 53 11.3578 ⋅ 21.9317 = 53 249.0964 = 0.2128 = 10 ⋅ 212 − 39 ⋅ 53 10 ⋅ 165 − ( 39 ) 2 ⋅ 10 ⋅ 329 − ( 53 ) 2 = 2120 − 2067 1650 − 1521 ⋅ 3290 − 2809 = 53 129 ⋅ 481 = 53 11.3578 ⋅ 21.9317 = 53 249.0964 = 0.2128 {:[=(10*212-39*53)/(sqrt(10*165-(39)^(2))*sqrt(10*329-(53)^(2)))],[=(2120-2067)/(sqrt(1650-1521)*sqrt(3290-2809))],[=(53)/(sqrt129*sqrt481)],[=(53)/(11.3578*21.9317)],[=(53)/(249.0964)],[=0.2128]:}\begin{aligned} & =\frac{10 \cdot 212-39 \cdot 53}{\sqrt{10 \cdot 165-(39)^2} \cdot \sqrt{10 \cdot 329-(53)^2}} \\ & =\frac{2120-2067}{\sqrt{1650-1521} \cdot \sqrt{3290-2809}} \\ & =\frac{53}{\sqrt{129} \cdot \sqrt{481}} \\ & =\frac{53}{11.3578 \cdot 21.9317} \\ & =\frac{53}{249.0964} \\ & =0.2128 \end{aligned}=10⋅212−39⋅5310⋅165−(39)2⋅10⋅329−(53)2=2120−20671650−1521⋅3290−2809=53129⋅481=5311.3578⋅21.9317=53249.0964=0.2128
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