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Miriam wants to test if her 10-sided die is fair, meaning she wants to test if some sides get rolled more often than others. She plans on recording how often each side appears in a series of rolls and carrying out a [tex]\chi^2[/tex] goodness-of-fit test on the results.

What is the smallest sample size Miriam can take to pass the large counts condition?

Answer :

Answer:50

Step-by-step explanation:

5(10)

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Rewritten by : Barada

The final answer is a sample size of 50 rolls.

1. Large Counts Condition:

- In order to perform a chi-square goodness-of-fit test, each expected count in the contingency table should be at least 5, according to the large counts condition.

- Since Miriam has a 10-sided die, there are 10 possible outcomes.

- To ensure each expected count is at least 5, she needs a total of at least [tex]\(10 \times 5 = 50\)[/tex] rolls.

2. Explanation:

- Suppose Miriam rolls the die [tex]\(n\)[/tex] times.

- The expected count for each side would ideally be [tex]\(n/10\)[/tex] since there are 10 sides and the die is fair.

- For the large counts condition, each expected count should be at least 5.

- Therefore, [tex]\(n/10 \geq 5\)[/tex] .

- Solving for [tex]\(n\)[/tex], we get [tex]\(n \geq 50\)[/tex] .

- Thus, the smallest sample size Miriam can take to pass the large counts condition is 50 rolls.