1. The frequencies of different blood types of 200 people who volunteered at a plasma center is given in the table. Blood Type O А frequency Are these four blood types equally likely? Use a = 0.05. АВ | Total 82 80 20 18 200 1. Identify the parame ters 2 Null hypothe sis 3. Altemative hypothesis 4. Test Statistics 6. Conclusion 5. Rejection region

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
icon
Related questions
Topic Video
Question
### Investigating Blood Type Frequencies at a Plasma Center

This exercise examines the frequencies of different blood types among 200 people who volunteered at a plasma center. The data is presented in the table below:

| **Blood Type** | **O** | **A** | **B** | **AB** | **Total** |
|:--------------:|:-----:|:-----:|:-----:|:------:|:---------:|
| **Frequency**  |   82  |   80  |   20  |   18   |    200    |

We aim to determine whether these four blood types are equally likely. We will conduct a hypothesis test at a significance level of \( \alpha = 0.05 \).

#### Step-by-Step Hypothesis Testing:

1. **Identify the Parameters:**

    The null and alternative hypotheses are based around the question of whether the four blood type distributions are equal in the population.

2. **Null Hypothesis (\( H_0 \)):**

    The null hypothesis posits that the proportions of the different blood types are equal. Mathematically, it can be expressed as:
    \[
    H_0: p_O = p_A = p_B = p_{AB} = \frac{1}{4}
    \]

3. **Alternative Hypothesis (\( H_A \)):**

    The alternative hypothesis is that at least one blood type proportion is different from the rest. Formally written as:
    \[
    H_A: \text{At least one } p_i \text{ is different}
    \]

4. **Test Statistic:**

    The test statistic for this goodness-of-fit test, typically a Chi-Square statistic, is calculated based on the observed frequencies and the expected frequencies under the null hypothesis.

5. **Rejection Region:**

    The rejection region is determined based on the Chi-Square distribution with degrees of freedom \( df = k - 1 \), where \( k \) is the number of categories (4 in this case). For \(\alpha = 0.05\) and \( df = 3 \), we refer to the critical value from Chi-Square tables.
    
    ![Rejection Region Graph](https://latex.codecogs.com/svg.image?\begin{array}{|c|c|c|c|}\hline&\textbf{df}&3\\\textbf{\
Transcribed Image Text:### Investigating Blood Type Frequencies at a Plasma Center This exercise examines the frequencies of different blood types among 200 people who volunteered at a plasma center. The data is presented in the table below: | **Blood Type** | **O** | **A** | **B** | **AB** | **Total** | |:--------------:|:-----:|:-----:|:-----:|:------:|:---------:| | **Frequency** | 82 | 80 | 20 | 18 | 200 | We aim to determine whether these four blood types are equally likely. We will conduct a hypothesis test at a significance level of \( \alpha = 0.05 \). #### Step-by-Step Hypothesis Testing: 1. **Identify the Parameters:** The null and alternative hypotheses are based around the question of whether the four blood type distributions are equal in the population. 2. **Null Hypothesis (\( H_0 \)):** The null hypothesis posits that the proportions of the different blood types are equal. Mathematically, it can be expressed as: \[ H_0: p_O = p_A = p_B = p_{AB} = \frac{1}{4} \] 3. **Alternative Hypothesis (\( H_A \)):** The alternative hypothesis is that at least one blood type proportion is different from the rest. Formally written as: \[ H_A: \text{At least one } p_i \text{ is different} \] 4. **Test Statistic:** The test statistic for this goodness-of-fit test, typically a Chi-Square statistic, is calculated based on the observed frequencies and the expected frequencies under the null hypothesis. 5. **Rejection Region:** The rejection region is determined based on the Chi-Square distribution with degrees of freedom \( df = k - 1 \), where \( k \) is the number of categories (4 in this case). For \(\alpha = 0.05\) and \( df = 3 \), we refer to the critical value from Chi-Square tables. ![Rejection Region Graph](https://latex.codecogs.com/svg.image?\begin{array}{|c|c|c|c|}\hline&\textbf{df}&3\\\textbf{\
Expert Solution
steps

Step by step

Solved in 2 steps

Blurred answer
Knowledge Booster
Hypothesis Tests and Confidence Intervals for Means
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.
Similar questions
Recommended textbooks for you
MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman