Intro

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					Public Health Institute Introductory Biostatistics for Healthcare Professionals
This workbook contains 10 worksheets including this introduction page Data and steps are provided for the following NORMDIST and NORMSDIST functions Confidence intervals of mean: CI_birthweight and CI_distance Paired t-test Two-sample t-test Confidence interval of proportion: CI_Prop1 Significance test of a proportion: Prop_test1 Confidence interval of the difference of two proportions: CI_Prop2 Significance test of difference of two proportions: Prop_test2

Birthweights at a certain hospital are normally distributed with mean = 112 oz. And Std. Dev. = 21 oz
Use NORMDIST and NORMSDIST to 1. Calculate the probability that an infant weighs more than 9 lbs (144 oz. )
1. Use NORMDIST: 2. Find the z-score for 144 oz 3. Use NORMSDIST

2. Calculate the probability that an infant weighs less than 6 lbs (96 oz)
1. Use NORMDIST: 2. Find the z-score for 96 oz 3. Use NORMSDIST

3. Calculate the probability that an infant weighs between 7 lbs (112 oz) and 8 lbs (128 oz)
1. Use NORMDIST: 2. Find the z-score for 112 oz 3. Find the z-score for 128 oz 4. Use NORMSDIST

Birthweights (oz) at a rural hospital are given for 40 infants. The standard deviation for infant birthweights is known: 21 oz. Construct a 95% CI and a 90% CI for the mean birthweight at this hospital
Birthweight (oz) 124 108 110 125 105 124 63 100 121 99 160 114 115 153 95 62 78 105 55 115 81 108 144 135 172 99 79 115 115 130 88 170 112 156 62 153 110 165 144 120

Lower Limit Average s SEM 95% CI z-coefficient z*SEM 90% CI z coefficient z* SEM 95% CI
21

Upper Limit

90% CI

Distance Walked in 6 Minutes after 90 days of Vest Therapy for 16 patients with COPD
Distance (ft) 1050 620 875 675 1150 600 650 625 775 750 950 625 775 1050 550 1150

lower limit Average SD SEM 95% CI t (15 df) t* SEM 90% CI t (15 df) t*SEM 95% CI 90% CI

upper limit

Use TINV function to obtain the t-value. The probability used is 1 - level of confidence (.95 or .90) The Deg_freedom = n-1

Paired t-test Distance walked in 6 Minutes before (Pre) and 90 days after (Post) treatment for 16 COPD patients
Subject 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Pre 1025 630 860 675 1120 590 540 615 745 730 945 630 770 1030 530 1120 Post 1050 620 875 675 1150 600 650 625 775 750 950 625 775 1050 550 1150 Under 'Tools' -> Data Analysis select 't-test paired two sample for Means' Highlight the 'Post' data in the Variable 1 range Highlight the 'Pre' data in the Variable 2 range Check the Labels box if you highlighted the column headers Excel will calculate the Post - Pre difference Indicate a cell for the Output table In the Output table highlight the p-value for the two-sided alternative hypothesis What is the Pre average distance walked? What is the Post average difference walked? What conclusion can you make?

Enter Output here

ative hypothesis

Two sample t-test Pain scores for patients in two groups. Group 1 received the standard treatment and group 2 received a new medication for Migraine headache pain.
Group 1 4 3 8 6 13 18 3 4 3 12 8 10 5 10 9 9 9 4 12 11 12 6 7 6 5 Group 2 5 2 1 5 1 2 8 1 6 3 3 1 10 4 2 6 1 2 2 3 13 2 8 9 4

Calculate the ratio of Standard deviations to check for equality of variance Under 'Tools' -> Data Analysis select 't-test two-sample assuming equal / unequal variance - whichever is approp Highlight the 'Group 1' data in the Variable 1 range Highlight the 'Group 2' data in the Variable 2 range Check the Labels box if you highlighted the column headers Indicate a cell for the Output table In the Output table highlight the p-value for the two-sided alternative hypothesis What is the Group 1 average pain score? What is the Group 2 average pain score? What conclusion can you make?

Enter Output here

Check for equality of variance Group 1 SD Group 2 SD

Ratio

headache pain.

equal variance - whichever is appropriate

95% Confidence Interval for the proportion of subjects that are nearsighted
Nearsighted Yes=1/No=0 yes 1 no 0 no 0 no 0 yes 1 yes 1 yes 1 yes 1 no 0 yes 1 yes 1 yes 1 yes 1 no 0 yes 1 yes 1 no 0 no 0 no 0 no 0 yes 1 no 0 yes 1 yes 1 no 0 yes 1 Count (n)= Sum = p= 1-p= SE(p)= 95% CI lower= upper= Summing the 1s and 0s gives the number with 'Yes'

Significance test - Is the proportion of subjects that are nearsighted equal to 0.5?
Null hypothesis: the true proportion of nearsighted in this population = 0.5 Alternative hypothesis: the true propotion of nearsighted in this population ≠ 0.5 Nearsighted Yes=1/No=0 yes 1 no 0 no 0 no 0 yes 1 yes 1 yes 1 yes no yes yes yes yes no yes yes no no no no yes no yes yes no yes 1 0 1 1 1 1 0 1 1 0 0 0 0 1 0 1 1 0 1 p

Count (n)= Sum (X)= p=

pO= - pO= z=
1-sided p-value= 2-sided p-value= SE(p)=

95% Confidence Interval for the difference in the proportion of diabetics between Urban and Rural patients
Diabetes-Urban 1 0 0 0 1 1 0 0 0 1 0 1 1 0 0 0 1 0 Diabetes-Rural 0 0 1 0 1 0 0 0 1 1 0 1 0 1 1 1

Urban Count = Sum = p (urban)= Count = Sum = p (rural)=

Rural

diff= SE(diff)= 95% CI lower= upper=

Significance test for the difference in the proportion of diabetics between Urban and Rural patients
Null hypothesis: the proportion of diabetics is equal in urban and rural clinics Alternative hypothesis: the proportion of diabetics is not equal in urban and rural clinics Diabetes-Urban 1 0 0 0 1 1 0 0 0 1 0 1 1 0 0 0 1 0 Diabetes-Rural 0 0 1 0 1 0 0 0 1 1 0 1 0 1 1 1

Urban Count U= Sum U= Urban p= Count R= Sum R= Rural p=

Rural

D = pU - p R = Combined p= SE (diff)

pu - pR =
1-p p(1-p)

z=
p-value=


				
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posted:11/8/2009
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