Use a paired t-test to determine if the baseline body mass index (BMI; kg/m2; bmi_baseline)
birthweightA smokingA gestational_ageA birthweightB smokingB gestational_ageB
3013 0 40.0 3395 1 37.1
2432 1 37.1 2944 0 38.2
3168 0 39.4 2993 1 35.4
2922 1 34.2 2906 1 32.0
2786 0 38.6 3152 0 33.6
2499 0 37.4 2911 1 37.9
2629 0 37.8 2707 1 36.4
2657 0 39.1 3410 0 37.7
3454 1 38.2 3277 0 36.7
3036 1 37.4 2901 0 39.8
2597 1 37.4 3193 0 35.1
2766 0 37.2 2977 1 37.8
3261 1 38.9 3122 0 35.2
3252 0 39.9 2744 1 34.9
2984 0 39.2 3165 1 37.5
3096 0 39.5 2530 0 37.0
2634 0 36.1 3092 0 36.4
2823 0 39.6 3084 1 39.9
2855 0 36.0 2678 0 32.7
3310 1 39.3 3265 0 40.2
2632 0 39.7 3025 0 33.0
2661 0 39.2 3054 0 39.4
2887 0 39.5 2832 0 35.8
2747 0 38.9 3253 0 37.2
2969 0 37.9 2912 0 36.7
3495 0 37.8 3178 0 34.8
2946 0 37.4 3349 0 37.2
2705 0 36.1 2718 1 40.0
3025 0 36.8 2978 0 40.4
3174 0 38.0 2838 1 37.1
2620 0 38.0 3192 0 38.4
3033 0 39.8 2407 0 38.4
2837 0 40.2 2817 1 34.9
2626 0 38.4 2989 1 37.4
2862 0 36.8 3134 1 39.3
3018 0 34.4 2830 1 36.1
3201 1 37.8 3024 0 40.2
3038 0 39.1 2429 1 34.8
2644 1 38.6 2727 0 35.1
2559 0 39.7 2810 0 40.2
2523 0 37.3 2928 1 37.1
2865 1 36.9 3174 1 34.7
2650 0 38.6 3547 0 39.8
2580 0 35.7 3096 0 36.6
3065 0 36.1 2839 0 36.2
3149 0 40.1 2779 0 36.3
3379 1 36.9 2591 0 38.5
3080 0 35.2 3031 1 32.3
2466 0 41.7 2859 1 38.4
3190 0 37.2 2744 1 34.3
Using the data on the sheet Q1, use a paired t-test to determine if the baseline body mass index (BMI; kg/m2; bmi_baseline) is different than the post-intervention BMI (bmi_post).
What is the p-value from the t-test?
Please interpret your finding in 1 to 2 sentences.
The data on sheet Q2Q3Q4 are from a (fictional) study with two independent groups of mother-newborn dyads. Each group had 50 participants.
birthweightA: birthweight (in grams) for group A
birthweightB: birthweight (in grams) for group B
smokingA: did this participant report smoking (1=yes, 0=no) for group A
smokingB: did this participant report smoking (1=yes, 0=no) for group B
gestational_ageA: gestational age (in weeks) for group A
gestational_ageB: gestational age (in weeks) for group B
FYI: gestational age is how long the pregnancy was before the child was born. 40 weeks is full term.
Birthweight
Is the variance of birthweight equal between the two groups? Provide your evidence and explain in 1 to 2 sentences.
(Hint: F.TEST(array1, array2) )
Determine if the birthweight for the children was different between the groups. Report the p-value and a brief interpretation of this finding.
Gestational age
Is the gestational age of birthweight equal between the two groups? Provide your evidence and explain in 1 to 2 sentences.
Determine if the gestational age for the children was different between the groups. Report the p-value and a brief interpretation of this finding.
The following steps will walk you through how to determine if the prevalence of smoking was different between the groups
For each group, count how many smokers and how many non-smokers and fill in the table below. You can use Excel’s countif statement to make this easier:
=countif(RANGE, 0) provides the number of non-smokers in the range selected
=countif(RANGE, 1) provides the number ofsmokers in the range selected
Observed Values
Smoker Non-smoker total
Group A Replace with # of smokers in group A Replace with # of non-smokers in group A 50
Group B Replace with # of smokers in group B Replace with # of non-smokers in group B 50
total Replace with total # of smokers (both groups added together) Replace with total # of non-smokers (both groups added together)
Calculate the expected values
Expected Values
Smoker Non-smoker total
Group A
Replace with
(total # of smokers*total number in Group A)/100)
Replace with
(total # of non-smokers*total number in Group A)/100)
50
Group B
Replace with
(total # of smokers*total number in Group B)/100)
Replace with
(total # of non-smokers*total number in Group B)/100)
50
total total # of smokers total # of non-smokers 100
Calculate the chi-squared p-value
=CHISQ.TEST(array1,array2)
where array1 is the 4 values in the center of the first table (observed values) and array2 is the 4 values in the center of the second table (expected values)
Briefly interpret your findings (1-2 sentences).
Study ID bmi_baseline bmi_post
1 22.7 23.0
2 24.7 22.7
3 25.8 23.5
4 26.1 23.2
5 21.5 21.3
6 21.6 24.2
7 27.4 24.0
8 21.9 23.9
9 22.7 23.3
10 29.4 28.6
11 23.9 22.3
12 20.9 23.6
13 25.1 24.2
14 28.2 28.2
15 28.1 27.7
16 25.6 27.6
17 25.3 23.5
18 24.4 22.8
19 27.4 24.0
20 27.7 26.0
21 26.5 27.9
22 23.2 19.7
23 22.4 21.6
24 26.7 21.7
25 27.0 24.5
26 27.0 27.0
27 33.6 34.7
28 28.0 28.4
29 23.2 21.3
30 26.8 29.7
31 26.6 28.4
32 25.0 24.6
33 24.4 22.4
34 18.7 18.5
35 27.3 24.5
36 25.4 24.2
37 31.0 32.7
38 21.9 20.2
39 29.8 28.5
40 26.7 26.0
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