# Report Properties
Owner: erj16b
Created: Nov 27, 2017
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State Population and Area Codes Part 3

Data set 1. State Population and Area Codes   [Info]

An appropriate level of signifigance for my data would be .01 since the data represents a strong, positive correlation.

The qualitative variable that will be observed is the state names. An appropriate sample size would be 30. The confidence interval for the sample proportion using the sample size 30 is -0.03 < p < 0.07.

Result 1: Resample Statistics Result 1   [Info]
Statistic: prop(State,Alabama)
ObservednMeanStd. dev.97.5th per.
0.02300.0213333330.0147935990.04

The margin of error is 0.05. Being that the sample proportion is 0.02, you subtract the margin of error, e, from the left side of the equation, and add the margin of error to the right side of the equation. This confidence interval equation shows that the range of specified values, sample proportion, lie between -0.03 and 0.07.

Result 2: Resample Statistics Result 2   [Info]

Looking at the histogram, the distribution of sample proportions is fairly normal. The frequencies of the proportions are evenly spread putting the peak towards the meadian and a gradual decrease on both sides.

The first quantitative variable being used is the population of states. An appropriate sample size would be 30. The confidence interval for the sample mean using the sample size 30 is 5,231,782.82 < M(mu) < 5,837,917.58 .

Result 3: Resample Statistics Result 3   [Info]
Statistic: mean(Population (2000))
ObservednMeanStd. dev.97.5th per.
5628483.5305534850.2829987.216999576.2

The margin of error is 303,067.38. Being that the sample mean is 5,534,850.2, you subtract the margin of error, e, from the left side of the equation, and add the margin of error to the right side of the equation. This confidence interval equation shows that the range of specified values, the sample mean, lie between 5,231,782.82 and 5,837,917.58 .

Result 4: Resample Statistics Result 4   [Info]

Looking at the histogram, the distribution of sample proportions is left skewed. There are fewer frequencies of states with smaller populations, but once the graph hits the peak, there is a gradual decrease on frequency, skewing the graph.

The probability of choosing another sample of 30 with a mean of at least 5,534,850.2 is 0.45508943.

Result 5: Normal Calculator Sample Mean Result 5   [Info]

Since the probability is almost half, there is a 50/50 chance of choosing another sample of 30 with a mean of at least 5,534,850.2. There is a fair chance of getting this number making the sample mean reasonable.

The second quantitative variable being used is the number of area codes in each state. An appropriate sample size would be 30. The confidence interval for the sample proportion using the sample size 30 is 0.121 < p < 0.451.

Result 6: Resample Statistics Result 6   [Info]
Statistic: prop(Number of Area Codes,1)
ObservednMeanStd. dev.97.5th per.
0.3300.2860.0677011690.42

The margin of error is 0.165. Being that the sample proportion is 0.286, you subtract the margin of error, e, from the left side of the equation, and add the margin of error to the right side of the equation. This confidence interval equation shows that the range of specified values, sample proportion, lie between -0.121 and 0.451.

Result 7: Resample Statistics Result 7   [Info]

Looking at the histogram, the distribution of sample proportions is right skewed. The peak is far away on the left side of the median and the rest of the data and frequencies slowly decreases with each bar making the graph right skewed.