A health care researcher would like to answer the following research question: On average, are for-profit nursing homes larger (based on total number of beds) than facilities of another type (non-profit and governmental)? What would be the appropriate test be to answer the research question above assuming 1) normal distribution and 2) skewed data distribution?Explain results, conclusions, assumptions based on the t-tests One-Sample StatisticsStd.DeviationStd. ErrorMeanMeanTotal Number of Beds400 108.1353.6422.682One-Sample TestTest Value = 095% Confidence Interval ofthe DifferenceSig. (2-tailed)MeanDifferencedfLowerUpperTotal Number of Beds40.316399.000108.133102.86113.41One-Sample Effect SizesStandardizera95% Confidence IntervalPointEstimateLowerUpperTotal Number of Beds Cohen's d53.6422.0161.8452.186Hedges' correction53.7432.0121.8412.182a. The denominator used in estimating the effect sizes.Cohen's d uses the sample standard deviation.Hedges' correction uses the sample standard deviation, plus a correction factor. One-Sample StatisticsStd.DeviationStd. ErrorMeanMeanfor profit=1, nonprofitand GV=0400.7075.45548.02277One-Sample TestTest Value = 095% Confidence Interval ofthe DifferenceSig. (2-tailed)MeanDifferencedfLowerUpperfor profit=1, nonprofitand GV=031.066399.000.70750.6627.7523One-Sample Effect SizesStandardizera95% Confidence IntervalPointEstimateLowerUpperfor profit=1, nonprofitand GV=0Cohen's d.455481.5531.4071.698Hedges' correction.456341.5501.4051.695a. The denominator used in estimating the effect sizes.Cohen's d uses the sample standard deviation.Hedges' correction uses the sample standard deviation, plus a correction factor.

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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A health care researcher would like to answer the following research question: On average, are for-profit nursing homes larger (based on total number of beds) than facilities of another type (non-profit and governmental)?

What would be the appropriate test be to answer the research question above assuming 1) normal distribution and 2) skewed data distribution?

Explain results, conclusions, assumptions based on the t-tests

One-Sample Statistics
Std.
Deviation
Std. Error
Mean
Mean
Total Number of Beds
400 108.13
53.642
2.682
One-Sample Test
Test Value = 0
95% Confidence Interval of
the Difference
Sig. (2-
tailed)
Mean
Difference
df
Lower
Upper
Total Number of Beds
40.316
399
.000
108.133
102.86
113.41
One-Sample Effect Sizes
Standardizera
95% Confidence Interval
Point
Estimate
Lower
Upper
Total Number of Beds Cohen's d
53.642
2.016
1.845
2.186
Hedges' correction
53.743
2.012
1.841
2.182
a. The denominator used in estimating the effect sizes.
Cohen's d uses the sample standard deviation.
Hedges' correction uses the sample standard deviation, plus a correction factor.

One-Sample Statistics
Std.
Deviation
Std. Error
Mean
Mean
for profit=1, nonprofit
and GV=0
400
.7075
.45548
.02277
One-Sample Test
Test Value = 0
95% Confidence Interval of
the Difference
Sig. (2-
tailed)
Mean
Difference
df
Lower
Upper
for profit=1, nonprofit
and GV=0
31.066
399
.000
.70750
.6627
.7523
One-Sample Effect Sizes
Standardizera
95% Confidence Interval
Point
Estimate
Lower
Upper
for profit=1, nonprofit
and GV=0
Cohen's d
.45548
1.553
1.407
1.698
Hedges' correction
.45634
1.550
1.405
1.695
a. The denominator used in estimating the effect sizes.
Cohen's d uses the sample standard deviation.
Hedges' correction uses the sample standard deviation, plus a correction factor.

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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