When they send out theirfundraising letter, a philanthropic organization typically gets a return from about 5% of the people on their mailing list. To see what the response rate might be in the future, they did a simulation using samples of size 20, 50, 100, and 200. For each sample size, they simulated 1000 mailings with success rate p=0.05 and constructed the histogram of the 1000 sample proportions, as shown in the accopmanying table. Explain how these histograms demonstrate what the Central Limit Theorem says about the sampling distribution model for sample proportions. Be sure to talk about center, shape, and spread. Fill in the blanks As the sample size increases, the center of the histogram ▼ (moves to the left), (moves to the right), (stays approximattly the same) the shape of the distribution ▼ (becomes more normal), (becomes less normal), (stays approximatley the same) and the variability in the sample proportions ▼ (decreases), (increases), (stays aproxamtley the same) These simulations ▼(appear), (do not appear) to demonstrate what the Central Limit Theorem says about the sampling distribution model for sample proportions.
When they send out theirfundraising letter, a philanthropic organization typically gets a return from about 5% of the people on their mailing list. To see what the response rate might be in the future, they did a simulation using samples of size 20, 50, 100, and 200. For each sample size, they simulated 1000 mailings with success rate p=0.05 and constructed the histogram of the 1000 sample proportions, as shown in the accopmanying table. Explain how these histograms demonstrate what the Central Limit Theorem says about the sampling distribution model for sample proportions. Be sure to talk about center, shape, and spread.
Fill in the blanks
As the
the shape of the distribution ▼ (becomes more normal), (becomes less normal), (stays approximatley the same)
and the variability in the sample proportions ▼ (decreases), (increases), (stays aproxamtley the same)
These simulations ▼(appear), (do not appear)
to demonstrate what the Central Limit Theorem says about the sampling distribution model for sample proportions.
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