SPSS Analytical Report

Running head: SPSS ANALYTICAL REPORT 1
SPSS Analytical Report
Name
Institution
Author’s Note
Word Count (1479) Excluding Tables, References and Appendix.

SPSS ANALYTICAL REPORT 2
SPSS Analytical Report
Methods
The descriptive statistics for scale variable (continuous) involve the use of measures
of central tendency and dispersion (Gravetter & Wallnau, 2016). However, for categorical
variables, the descriptive statistics used in the analysis are frequency and count(percentages).
Next for the study of the relationship between categorical variables, the best approach is a
Chi-square test of association alongside crosstabulations (Ali & Bhaskar, 2016). In order to
describe the relationship between one categorical and one quantitative variable (Continuous
or discrete), we use a one-way analysis of variance (ANOVA) approach (Bowers, 2019).
Further, to describe the relationship between the quantitative variable (Continuous), we use
Pearson correlation coefficient statistics (Schober, Boer & Schwarte, 2018).
The last two sections of the report involve regression analysis and test of hypothesis.
Multiple linear regression was used to establish a direct link between response and
independent variables. The model fits interpretation was based on R-square value, and overall
goodness of fit was established on the F-statistic. Variables whose slope (parameters
estimate) are significant were interpreted based on the regression model and the type of the
variable. In testing for mean differences, student t-test was used under the assumption of
unequal variances. Finally, throughout the report, the decision criteria for rejection of null
hypothesis is alpha of 5% (that is 95% significance level) and p-value of the estimates.
In testing the average difference in two continuous variables with unknown standard
deviation, we use t-test (Kim, 2015). The hypothesis takes the following form:
H0: μ1 = μ2 ("the two-population means are equal")
H1: μ1 ≠ μ2 ("the two-population means are not equal")
Where μ1 and μ2 are the population means of Ward’s triangle BMD and the L1 BMD
respectively.

SPSS ANALYTICAL REPORT 3
Results
The results are presented in tables and description of key SPSS outputs under each
subheading.
Descriptive Statistics of Variables
This section entails descriptive statistics for the variables under investigation.
Demographic Variables
The demographic variables include Age (years), sex, ethnicity and participants
mothers' history of a fractured hip. The youngest participant at the time of screening was 20
year while the oldest was 80 years, giving a range of 60 years. Further, the average age of the
participants was 50 years, with a corresponding standard deviation of 18 years. The standard
deviation implies that 68% of the participants are aged between 32 years and 78 years. Next,
Table 1 shows the frequency and per cent for the sex at the birth of the participants.
Table 1: Frequency (count) for Sex at Birth
Sex Frequency (count) Percent (%)
Male 521 50.4
Female 512 49.6
Total 1033 100.0
Source: Author (2019)
Male participants form 50.4% of the total population, while the remaining 49.6%
represent female participants. Table 2 shows the frequency and per cent for the race/ethnicity
of the participants.
Table 2: Frequency (count) for Race/Ethnicity
Race/Ethnicity Frequency (count) Percent (%)
Mexican American 453 43.9
Other Hispanic 113 10.9
Non-Hispanic white 185 17.9
Non-Hispanic black 231 22.4
Other race 51 4.9
Total 1033 100.0
Source: Author (2019)

SPSS ANALYTICAL REPORT 4
Mexican American, Other Hispanic, Non-Hispanic white, Non-Hispanic black, and Other
race forms 43.9%, 10.9%, 17.9%, 22.4%, and 4.9% respectively. Table 3 shows the
frequency and per cent for mothers' hip structure history of the participants.
Table 3: Frequency (count) for Did mother ever fracture hip
Sex Frequency (count) Percent (%)
No 949 91.8
Yes 42 4.1
Refused/don’t know 42 4.1
Total 1033 100.0
Source: Author (2019)
Participants whose mothers had hip fracture form 91.8%, those whose mothers did not
have fractured hip form the remaining 4.1% and 4.1% do not know whether their mothers had
a hip fracture or not.
Lifestyle Variables
The lifestyle variables are body mass index (BMI), and Participants Ever taken
prednisone or cortisone daily. The lowest BMI reported was 14.86 kg/m while the highest
was 73.43 kg/m. Additionally, the average BMI of the participants was 29.4003 kg/m with a
corresponding standard deviation of 7.03193 kg/m (Gravetter & Wallnau, 2016). The
standard deviation implies that 68% of the participants have a BMI between 22.36 kg/m and
36.43 kg/m. Table 4 shows the percentage of participants ever taken prednisone or cortisone
daily.
Table 4: Frequency (count) for ever taken prednisone or cortisone daily
Sex Frequency (count) Percent (%)
No 973 94.2
Yes 52 5.0
Refused/don’t know 8 0.8
Total 1033 100.0
Source: Author (2019)