Pessimistic: n = 10, M = 2.9, SS = 40.9, s? = 4.54 Optimistic: n = 10, M = 6.8, SS = 25.6, s? = 2.84 %3D %3D %3D Step 1: State the hypotheses. (Select A, B, or C) (A) (B) (C) HO: μι- μ2#0 H1: μι- μ2 = 0 HO: µ1 # µ2 H0: μι-μ2 = 0 Η 1: μι- μ2 + 0 H1: μι- μ2 Hypotheses Step 2: State the critical values. df = t-critical value = +/- (use 3 places to the right of the decimal point) Step 3: Compute the test statistic: Summary Statistics Pooled Variance: Sp2 = (Use 3 dec. places) Pooled Standard Deviation: Sp = (Use 3 dec. places)

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Chapter1: Starting With Matlab
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Step 1: State the hypotheses.
(Select A, B, or C)

Hypotheses = 

Step 2: State the critical values.

df = 

t-critical value = +/- 
(use 3 places to the right of the decimal point)

Step 3: Compute the test statistic: Summary Statistics

Pooled Variance: sP2 = 
(Use 3 dec. places)

Pooled Standard Deviation: sP = 
(Use 3 dec. places)

### Statistical Hypothesis Testing: Comparing Two Means

**Given Data:**
- **Pessimistic Group:**
  - Sample size (n) = 10
  - Mean (M) = 2.9
  - Sum of Squares (SS) = 40.9
  - Variance (\(s^2\)) = 4.54
- **Optimistic Group:**
  - Sample size (n) = 10
  - Mean (M) = 6.8
  - Sum of Squares (SS) = 25.6
  - Variance (\(s^2\)) = 2.84

### Step-by-Step Process

**Step 1: State the Hypotheses. (Select A, B, or C)**

- **(A)**
  - \(H_0: \mu_1 - \mu_2 = 0\)
  - \(H_1: \mu_1 - \mu_2 \neq 0\)
- **(B)**
  - \(H_0: \mu_1 \neq \mu_2\)
  - \(H_1: \mu_1 = \mu_2\)
- **(C)**
  - \(H_0: \mu_1 - \mu_2 \neq 0\)
  - \(H_1: \mu_1 - \mu_2 = 0\)

*Hypotheses:* [ ] (Select one option from A, B, or C)

**Step 2: State the Critical Values.**

- Degrees of Freedom (\(df\)): [ ]  
- t-critical value: \(\pm\) [ ]  
  *(Use three decimal places)*

**Step 3: Compute the Test Statistic: Summary Statistics**

- **Pooled Variance (\(s^2_p\))** = [ ]  
  *(Use three decimal places)*

- **Pooled Standard Deviation (\(s_p\))** = [ ]  
  *(Use three decimal places)*

This template guides you through the process of setting up hypotheses, determining critical values for hypothesis testing, and calculating test statistics using summary statistics.
Transcribed Image Text:### Statistical Hypothesis Testing: Comparing Two Means **Given Data:** - **Pessimistic Group:** - Sample size (n) = 10 - Mean (M) = 2.9 - Sum of Squares (SS) = 40.9 - Variance (\(s^2\)) = 4.54 - **Optimistic Group:** - Sample size (n) = 10 - Mean (M) = 6.8 - Sum of Squares (SS) = 25.6 - Variance (\(s^2\)) = 2.84 ### Step-by-Step Process **Step 1: State the Hypotheses. (Select A, B, or C)** - **(A)** - \(H_0: \mu_1 - \mu_2 = 0\) - \(H_1: \mu_1 - \mu_2 \neq 0\) - **(B)** - \(H_0: \mu_1 \neq \mu_2\) - \(H_1: \mu_1 = \mu_2\) - **(C)** - \(H_0: \mu_1 - \mu_2 \neq 0\) - \(H_1: \mu_1 - \mu_2 = 0\) *Hypotheses:* [ ] (Select one option from A, B, or C) **Step 2: State the Critical Values.** - Degrees of Freedom (\(df\)): [ ] - t-critical value: \(\pm\) [ ] *(Use three decimal places)* **Step 3: Compute the Test Statistic: Summary Statistics** - **Pooled Variance (\(s^2_p\))** = [ ] *(Use three decimal places)* - **Pooled Standard Deviation (\(s_p\))** = [ ] *(Use three decimal places)* This template guides you through the process of setting up hypotheses, determining critical values for hypothesis testing, and calculating test statistics using summary statistics.
**Research Study on Recycling Habits and Attitudes**

**Q21. Individual Actions and Environmental Health**

Individual actions can significantly impact the overall health of our planet. A researcher focused on evaluating environmentally friendly behaviors examined how often people recycle (per month), based on whether they have a predominantly optimistic or pessimistic attitude toward eco-friendly behaviors. This is a hypothetical study, and the results are shown in the table below. Use this data to test the hypothesis that the number of complaints changed after implementing a new policy, applying a two-tailed test with a significance level of α = .05.

**Recycling Frequency Based on Attitude**

| Pessimistic | Optimistic |
|-------------|------------|
| 3           | 4          |
| 0           | 9          |
| 4           | 6          |
| 2           | 8          |
| 1           | 9          |
| 6           | 5          |
| 5           | 8          |
| 0           | 6          |
| 5           | 7          |

**Statistical Data Summary**

- **Pessimistic Group:**
  - Number of participants (n) = 10
  - Mean (M) = 2.9
  - Sum of Squares (SS) = 40.9
  - Variance (s²) = 4.54

- **Optimistic Group:**
  - Number of participants (n) = 10
  - Mean (M) = 6.8
  - Sum of Squares (SS) = 25.6
  - Variance (s²) = 2.84

This study aims to explore whether an optimistic attitude correlates with increased recycling behavior, which could indicate fewer complaints about environmental initiatives. The analysis uses a rigorous statistical approach to draw meaningful conclusions.
Transcribed Image Text:**Research Study on Recycling Habits and Attitudes** **Q21. Individual Actions and Environmental Health** Individual actions can significantly impact the overall health of our planet. A researcher focused on evaluating environmentally friendly behaviors examined how often people recycle (per month), based on whether they have a predominantly optimistic or pessimistic attitude toward eco-friendly behaviors. This is a hypothetical study, and the results are shown in the table below. Use this data to test the hypothesis that the number of complaints changed after implementing a new policy, applying a two-tailed test with a significance level of α = .05. **Recycling Frequency Based on Attitude** | Pessimistic | Optimistic | |-------------|------------| | 3 | 4 | | 0 | 9 | | 4 | 6 | | 2 | 8 | | 1 | 9 | | 6 | 5 | | 5 | 8 | | 0 | 6 | | 5 | 7 | **Statistical Data Summary** - **Pessimistic Group:** - Number of participants (n) = 10 - Mean (M) = 2.9 - Sum of Squares (SS) = 40.9 - Variance (s²) = 4.54 - **Optimistic Group:** - Number of participants (n) = 10 - Mean (M) = 6.8 - Sum of Squares (SS) = 25.6 - Variance (s²) = 2.84 This study aims to explore whether an optimistic attitude correlates with increased recycling behavior, which could indicate fewer complaints about environmental initiatives. The analysis uses a rigorous statistical approach to draw meaningful conclusions.
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