Suppose you want to estimate the mean bowling score for all participants in a large bowl he distribution of bowling scores for a random sample of 18 bowlers in the league.

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Suppose you want to estimate the mean bowling score for all participants in a large bowling league. The stemplot summarizes
the distribution of bowling scores for a random sample of 18 bowlers in the league.
2410
24 668
25 001124
25 55688
26 01
26 5
Key: 26 | 5 = A bowler that scored 265.
Is the Normal/Large Sample condition met? Explain.
Yes! Although the sample size is small, the graph of
the sample data shows no strong skewness or
outliers.
No, the sample size is small and the graph of the
sample data is strongly skewed to the right with at
least one high outlier.
No, the sample size is small, n = 18 < 30.
There is not enough information provided to
determine if the Normal/Large Sample condition is
met.
Yes, the data come from a normally distributed
population.
Transcribed Image Text:Suppose you want to estimate the mean bowling score for all participants in a large bowling league. The stemplot summarizes the distribution of bowling scores for a random sample of 18 bowlers in the league. 2410 24 668 25 001124 25 55688 26 01 26 5 Key: 26 | 5 = A bowler that scored 265. Is the Normal/Large Sample condition met? Explain. Yes! Although the sample size is small, the graph of the sample data shows no strong skewness or outliers. No, the sample size is small and the graph of the sample data is strongly skewed to the right with at least one high outlier. No, the sample size is small, n = 18 < 30. There is not enough information provided to determine if the Normal/Large Sample condition is met. Yes, the data come from a normally distributed population.
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