User Generated

pbpbobb2019

Mathematics

Walden University

Description

Overview

Blood pressure is the force of blood pushing against the walls of the arteries that carry blood from your heart to other parts of your body. Blood pressure normally rises and falls throughout the day, but it can damage your heart and cause health problems if it stays high for a long time. Keeping your blood pressure levels in a healthy range usually involves taking medications among other things.

In this part, you will work with a set of data that is obtained by testing a new drug for blood pressure. The data consists of information collected on 50 patients on the following variables:

• Subject: Patient
• Treatment: Two levels. 0 for Placebo and 1 for treatment group
• Gender: Male or Female
• Fam-Hist-BP: Paternal Side - PS, Maternal Side - MS,
Both Sides – BS, None on both sides (or not known) – N
• Age: Age of patient
• BP-Before-Exp: Blood Pressure before experiment
• BP-After- Exp: Blood Pressure after experiment

Do the following

• Data: Download the NEW DRUG DATA (see attachment) and study the data.
• Review Using the Import Data Utility in SAS Studio (Links to an external site.)to learn how to import Excel data files into SAS Studio.
• Required Action: Based on the data set provided, produce the following output with SAS (or SPSS):
• Generate frequency tables for three categorical variables.
• Generate at least two different cross-tabulations.
• Generate a pareto chart for the categorical variable Fam-Hist-BP.
• Find the five number summary, mean, and standard deviation for three quantitative variables.
• Generate a side by side boxplot to compare the variables BP-Before-Exp and BP-After-Exp.
• Generate a histogram for each of the quantitative variables.
• Generate a scatterplot to display the relationship and find the correlation between Age and BP-Before-Exp.
• Generate a scatterplot to display the relationship and find the correlation between BP-Before-Exp and BP-After-Exp.

Unformatted Attachment Preview

Subject D1 D2 D3 D4 D5 D6 D7 D8 D9 D10 D11 D12 D13 D14 D15 D16 D17 D18 D19 D20 D21 D22 D23 D24 D25 D26 D27 D28 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 C16 C17 A18 Treatment 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Gender F F M F F M M M F F F M M F M M F F F M M M F M F M F F F F M M M F F M F F M M F F M M M F Fam-Hist-BP Age PS N MS MS MS BS PS N N PS PS MS N N MS PS BS BS MS PS MS BS N N PS PS BS MS MS BS N PS N BS MS PS N PS MS N BS MS PS BS PS N 65 59 60 54 65 57 69 62 49 45 65 62 64 68 70 66 65 63 61 63 69 56 58 46 56 64 61 66 63 56 54 69 75 62 61 59 73 57 48 64 61 66 57 65 63 51 BP-Before-Exp BP-After-Exp 103.3 80.5 93.6 85.9 92 85.2 93 87.8 95.4 85.3 109.6 94.2 97.9 83.9 96 85 98.4 86.3 98.4 90 95.5 85.2 91.7 87.9 98.6 84.6 98 83.8 96.4 85.5 104.4 93 111.7 85.4 108.6 84.8 99.1 82.4 106.8 88.7 111.5 86.5 97.4 82.4 87.5 78 98.1 83.8 98.6 87 99.1 86.3 96.4 87.6 101.2 84.8 97.4 93.1 97.2 92.4 98.8 94.6 98.4 92.3 89.8 89.3 103.4 99.7 90.1 88.4 93.7 90.4 96.4 91.1 98.6 90.5 95.2 90.4 95 89.3 97.4 93.8 97.4 92.6 101.6 96.9 101.2 98.9 97.5 89.9 92.2 86.2 A19 A20 A21 A22 0 0 0 0 M F F M N PS BS MS 68 65 65 64 Source: Inter-University Consortium for Political and Social Research (ICPSR) 96.6 96.9 102.6 99.5 92.6 90.4 91.5 93.8 BP-Before-Exp BP-After-Exp BP-Before-Exp BP-After-Exp
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New Drug Data Analysis
For the study, analysis was carried out based on the New Drug Dataset that was obtained from
testing the effectiveness of a new drug in treating blood pressure. The data consisted of
information collected on 50 patients on the following variables: Subject: Patient, Treatment:
Two levels. 0 for Placebo and 1 for treatment group, Gender: Male or Female, Fam-Hist-BP:
Paternal Side - PS, Maternal Side - MS, Both Sides – BS, None on both sides (or not known) –
N, Age: Age of patient, BP-Before-Exp: Blood Pressure before experiment, and BP-After- Exp:
Blood Pressure after experiment. Analysis involved carrying out frequency analysis and
obtaining descriptive statistics from the data. Various visualizations were also obtained from the
data. This paper presents findings from the analysis.
Frequency Tables for three categorical variables
There were three main categorical variables in the study. The variables included; treatment,
gender and family history. Frequency tables were computed for the three variables. The results
obtained were as below.
Treatment
Treatment Frequency Percent

Cumulative Cumulative
Frequency
Percent

0

22

44.00

22

44.00

1

28

56.00

50

100.00

Table 1: Frequency Table for treatment variable

Gender
Cumulative Cumulative
Gender Frequency Percent Frequency
Percent
F

26

52.00

26

52.00

M

24

48.00

50

100.00

Table 2: Frequency Table for Gender variable

Fam-Hist-BP
Fam-Hist-BP

Frequency Percent

Cumulative Cumulative
Frequency
Percent

BS

10

20.00

10

20.00

MS

13

26.00

23

46.00

N

13

26.00

36

72.00

PS

14

28.00

50

100.00

Table 3: Frequency Table for Family History variable
Based on the analysis of the three categorical variables, there appears to be a somewhat equal
representation of participants in terms ...

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