Research question: we are interested in studying the association between the age of students and the way they watched the lecture (livestream or in class) in the population under consideration.
Please complete the following tables, calculating the values of A and B.

Observed count
      | 1 (less than 19) | 2 (19-21) | 3 (22-24) | 4 (more than 24) | Sum
False | 16               | 24        | 18        | 13               | 71 
True  | 34               | A=***     | 17        | 7                | 79 
Sum   | 50               | 45        | 35        | 20               | 150

Expected count
      | 1 (less than 19) | 2 (19-21) | 3 (22-24) | 4 (more than 24)
False | 23.667           | 21.3      | B=***     | 9.467           
True  | 26.333           | 23.7      | 18.433    | 10.533          

chi-squared
      | 1 (less than 19) | 2 (19-21) | 3 (22-24) | 4 (more than 24)
False | 2.484            | 0.342     | 0.124     | 1.319           
True  | 2.232            | 0.308     | 0.111     | 1.185           
A [integer]:	Answer 1 Question 1
B [use at least 3dp]:	Answer 2 Question 1


Let's go step by step to find the missing values \( A \) and \( B \) for the given tables.

### 1. **Finding \( A \):**

In the "Observed count" table, the sum of students in the "True" row is given as 79. So, we can determine \( A \) by subtracting the other known values from 79:

\[
A = 79 - (34 + 17 + 7) = 79 - 58 = 21
\]

Thus, \( A = 21 \).

### 2. **Finding \( B \):**

In the "Expected count" table, we need to calculate \( B \), the expected count for "False" in the "3 (22-24)" age group. 

The formula for calculating the expected count in a contingency table is:

\[
E_{ij} = \frac{(\text{Row Total}_i) \times (\text{Column Total}_j)}{\text{Grand Total}}
\]

For the "False" row in the "22-24" column:
- Row total for "False" = 71
- Column total for "22-24" = 35
- Grand total = 150

So, the expected count \( B \) is:

\[
B = \frac{71 \times 35}{150} = \frac{2485}{150} = 16.567
\]

Thus, \( B = 16.567 \) (rounded to 3 decimal places).

### Final Answers:
1. \( A = 21 \)
2. \( B = 16.567 \)

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Would you like more details or have any questions about the calculations? Here are 5 related questions for further exploration:

1. How is the chi-squared statistic calculated using observed and expected values?
2. What does a high chi-squared value indicate in this context?
3. Can the degrees of freedom in this chi-squared test be calculated?
4. What assumptions are made when using the chi-squared test for independence?
5. How would the conclusion change if \( A \) and \( B \) were significantly different from the calculated values?

**Tip:** When working with contingency tables, always double-check that the row and column sums match the totals in order to avoid errors in calculations.

Research question: we are interested in studying the association between the age of students and the way they watched the lecture (livestream or in class) in the population under consideration. Please complete the following tables, calculating the values of A and B.

This solution explores the association between students' ages and their method of lecture attendance (livestream or in class) using a chi-square test. Learn to calculate expected counts and use the chi-squared formula. Suitable for college-level statistics students.

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