1
Liberty University
The Relationship of Sex & Age to the Duration of Daily Prayer
Time
HLTH 511
2
Introduction
The quantity of time that men and women devote to silent prayer each day is a topic of great
interest. The importance and length of prayer time are not known to be affected by age, sex, or
marital status. These two studies questions 1. The impact of age on prayer time and 2. The role
that sex plays in how much time people spend in prayer and meditation each day—are covered in
the research that follows. The amount of time devoted to private or social prayer may either
significantly rise or drastically decrease as a person matures, according to prior research. This can
be assessed on a daily or weekly basis, with most of the time taking place in a church context.
Those who gradually increase their prayer frequency are the ones who typically exhibit this. Due
to the increase in spiritual strength that comes with age, data also hints that one's sexual
orientation (sex) may have an impact on how much time is spent praying. In the spiritual and
practical growth of prayer, which is dependent on the person's sex, societal standards also play a
part. In contrast to what is typically permitted for females, males are exposed to higher amounts
of stress.
Studies on the relationship between prayer and sex have found that the length of time
spent praying over the Bible depends on the person's sex. Additionally, there is evidence that
more prayer time leads to improvements in mental health issues, including anxiety and sadness.
The foundation of this study is a "Sense of Coherence Theory" that discusses the ability of
humans as a whole to adapt, and it shows that prayer and personal health are positively
correlated in people of all ages. It is possible to have a better understanding of this relationship
using scientifically validated approaches, which may then be applied to a number of therapeutic
scenarios.
An optimistic and in-control feeling are both characteristics of coherence. This theory is
composed of the following three components: comprehension, manageability, and
meaningfulness. The way people respond to issues that come up during their lives is measured
by this idea, which Aaron Antonovsky established in 1987. The first analysis focuses on
locating several elements that fall under the category of sources of resistance. 1 Another
distinction that may be drawn is between methods of problem-solving that are concrete or
relational, which can be divided into adapting and coping strategies.
3
Using statistical tests to assess and define the research questions and come up with the
right answers will be a key component of this body of work, which will build on ideas covered in
earlier chapters. This information will be utilized to implement both private and public activities
that support the growth of the population's prayer life and an age-related rise in devotion to God.
This observational research's objective is to aid in the identification of a statistically
significant age-relationship between daily prayer time and time spent in age. The statistical
analysis of the link between sex and the duration of prayer as well as any potential connections
among the two.
Methods
It is assumed that there will be a linear link between age and prayer time as well as sex
and the quantity of daily prayer time when deciding the analytical solution to the study questions.
A variety of parametric and non-parametric tests should be used to resolve the research issues
because they each contain a dependent and an independent variable in their setup. This comes
after the normalcy of each test has been established.
Design
To determine the average daily time spent in prayer, age at the time of management, and
sex, surveys were given out by researchers and volunteers. The lead investigator oversaw the
completion of these surveys in a semi-private setting. To maintain the integrity of the data, no
help was given to the individuals during their completion of the surveys.
Sample
The study's conclusion was reached using a convenience sample of college students and
professors. All of the tests and analyses that were carried out on these subjects were done at their
own volition and without restriction. It was not implied that there would be any financial or
material gain.
Equipment
The questionnaires were made, filled out, and data collected using clipboards, pencils, and
copy paper. To answer the study questions, the acquired data were analyzed using SPSS
(Statistical Package for the Social Sciences) software.
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Data Collection & Analysis
Before being analyzed and included in the end result, numerical data was gathered and
kept in a safe place. This information was gathered from an informal or nonstatistical population
of students, ranging in age from freshmen to those who had completed their doctorate degrees.
Statistical Procedures
The sample was used to compute the mean, median, standard deviation, minimum, and
maximum data distribution metrics. We searched for outliers across the whole body of data. To
assess the amplitude and statistical significance of the associations between age and sex during
daily prayer time, parametric and/or non-parametric test correlations were taken into account at
each step. When the difference in age and sex differed in significance, both parametric and
nonparametric comparisons of the mean time were used. The results part of this publication
provided a determination of whether parametric or non-parametric inferential tests were required.
Hypotheses Tested
Null Hypothesis: p (rho) = 0 There is no significant relationship between age and prayer time.
Alternative Hypothesis: p (rho) not = to 0 There is a significant relationship between age and
prayer time.
Null Hypothesis: u (mu) Male – u (mu) Female = 0 There is no significant difference between
mean sex (Gender) and time spent in prayer.
Alternative Hypothesis: u(mu) Male- u (Female) Not = to 0 There is a significant difference
between the mean sex (gender) and time spent in prayer.
Both hypotheses tested at the scientific standard of 0.05 level of significance.
Results
Is there a relationship between an individual's age and the amount of time they spend praying?
The best test to utilize in this circumstance is a parametric test.
Is there a significant difference between how long men and women (separated by gender) spend
in prayer each day?
The best statistical test for this research question is a parametric test.
5
In comparison to non-parametric testing, these test statistics are more potent and likely to
identify anomalies. If there is a difference, it will be mentioned. Furthermore, parametric testing
greatly increases the amount of data obtained. Consequently, a large enough sample size is
required for the test to show a difference. The tests that were run to get the supplied data's
analytical result are listed below.
Test What test is used Number of variables Parametric or non-
parametric tests
t-test Difference 2 Parametric
Mann-Whitney Difference 2 Non-Parametric
Pearson Correlation Relationship 2 Parametric
Spearman Correlation Relationship 2 Non-Parametric
Statistics
Age
Age
(Years) Time Gender
NValid 144 144 144
Missin
g
0 0 0
Mean 20.3124 44.6692 1.5000
Mode 21.36a35.03 2.00a
Std. Deviation 1.47162 5.94026 .50175
Minimum 16.40 31.00 1.00
Maximum 24.35 57.95 2.00
a. Multiple modes exist. The smallest value is
shown
Frequency
Frequency
Histogram
for
Gender
Male
200
Age
(Years)
Histogram
for
Gender=
Female
1600
1800
00
2200
24.00
Age
(Years)
6
7
Young adults and people in their middle years are consistently found to spend the most time
praying each day, as illustrated by the previous photographs. The lack of correlation between
gender and age in the frequency and prevalence of prayer further strengthens this bond
between men and women. Since men are more likely than women to deal with harsher and
more stressful conditions, studies have found that men pray a little more frequently than
women. When it comes to prayer and the frequency of prayers, women have more endurance
than men as they age. This contrasts with men, who have more endurance when they pray less
frequently but for longer periods of time. The graph below demonstrates that men start
praying for extended amounts of time on average at a little earlier age than women do. This
shows that women start praying more frequently during the day and that they finish their
larger periods of prayer earlier than men their own age.
8
Pearson Correlation Time
Age
(Years)
Time
Age
(Years)
Pearson
Correlation
1 .994**
Sig. (2-tailed) <.001
N
Pearson
Correlation
144
.994**
144
1
Sig. (2-tailed) <.001
N144 144
**. Correlation is significant at the 0.01 level (2-
tailed).
Mann-Whitney Test
Ranks
Gende
r N
Mean
Rank
Sum of
Ranks
Age
(Years)
Time
Male 72 72.99 5255.50
Femal
e
72 72.01 5184.50
Total
Male
144
72 72.97 5253.50
Femal
e
72 72.03 5186.50
Total 144
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Test Statistics
Age
(Years) Time
Mann-Whitney U 2556.500 2558.50
0
Wilcoxon W 5184.500 5186.50
0
Z-.142 -.134
Asymp. Sig. (2-
tailed)
.887 .894
a. Grouping Variable: Gender
Paired Samnles Statistics
Mean N
Std.
Deviation
Std. Error
Mean
Pair
1
Time 44.6692 144 5.94026 .49502
Age
(Years)
20.3124 144 1.47162 .12264
Paired Samnles Correlations
N
Correlatio
n
Significance
One-Sided Two-Sided
p p
Pair
1
Time & Age
(Years)
144 .994 <.001 <.001
Paired Samnles Test
Paired Differences
Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair Time - Age 24.356 4.48023 .37335 23.61873 25.09474
1 (Years) 74
Paired Samnles Test
t df
Significance
One- Two-
Sided p Sided p
Pair 1 Time - 65.238 143 <.001 <.001
10
Age
(Years)
Paired Samnles Effect
Sizes 95% Confidence
Standardi
zera
Point
Estimate
Interval
Lower Upper
Pair Time - Age Cohen's d 4.48023 5.436 4.785 6.086
1 (Years) Hedges'
correction
4.50390 5.408 4.760 6.054
a. The denominator used in estimating the effect sizes.
Cohen's d uses the sample standard deviation of the mean difference.
Hedges' correction uses the sample standard deviation of the mean difference, plus
a correction factor.
Correlations
Tim
e
Age
(Years)
Spearman's Time
rho
Correlation
Coefficient
1.000 1.000**
Age
(Years)
Sig. (2-tailed) . .000
N
Correlation
Coefficient
144
1.000**
144
1.000
Sig. (2-tailed) .000 .
N144 144
12
**. Correlation is significant at the 0.01 level (2-tailed).
Gender
Gender
Frequen
cy Percent
Valid
Percent
Cumulative
Percent
Valid Male 72 50.0 50.0 50.0
Femal
e
72 50.0 50.0 100.0
Total 144 100.0 100.0
Descrintives
Gender Statistic
Std.
Error
Time Male
Femal
e
Mean
95% Confidence
Interval for Mean
5% Trimmed
Mean Median
Variance
Std. Deviation
Minimum
Maximum
Range
Interquartile Range
Skewness
Kurtosis
Mean
95% Confidence
Interval for Mean
5% Trimmed
Mean Median
Variance
Std. Deviation
44.7462 .70264
Lower 43.3452
Bound
Upper 46.1473
Bound
44.6619
44.4700
35.547
5.96214
31.85
57.95
26.10
7.50
.221 .283
-.272 .559
44.5921 .70229
Lower 43.1918
Bound
Upper 45.9924
Bound
44.5526
44.3600
35.511
5.95913
13
Minimum 31.00
Maximum 57.64
Range 26.64
Interquartile Range 7.72
Skewness .130 .283
Kurtosis -.199 .559
Statistical Analysis:
Gende
Case Processing Summary
Cases
Valid Missing Total
r N Percent N Percent N Percent
Time Male 72 100.0% 0 0.0% 72 100.0%
Femal
e
72 100.0% 0 0.0% 72 100.0%
Gende
Tests of Normality
Kolmogorov-SmirnovaShapiro-Wilk
r Statistic df Sig. Statistic df Sig.
Time Male .057 72 .200*.987 72 .690
Femal
e
.050 72 .200*.991 72 .885
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
14
Time Spent in prayer based on gender.
15
Correlations
Time Gender
Time Pearson 1 -.013
Correlation
Sig. (2-tailed) .877
N144 144
Gend Pearson -.013 1
er Correlation
Sig. (2-tailed) .877
N144 144
Mann-Whitney Test
Ranks
Gende
r N
Mean
Rank
Sum of
Ranks
Time Male 72 72.97 5253.50
Femal
e
72 72.03 5186.50
Total 144
Test Statistics
a
Time
Mann-Whitney U 2558.50
0
Wilcoxon W 5186.50
0
Z-.134
Asymp. Sig. (2-
tailed)
.894
a. Grouping Variable: Gender
Correlations
Time Gender
Spearman's rho Time Correlation Coefficient 1.000 -.011
Sig. (2-tailed) . .894
N144 144
Gender Correlation Coefficient -.011 1.000
Sig. (2-tailed) .894 .
16
Correlations
Gender
Age
(Years) Time
Spearman's Gender
rho
Correlation
Coefficient
1.000 -.012 -.011
Sig. (2-tailed) . .888 .894
N144 144 144
Age Correlation -.012 1.000 1.000**
(Years) Coefficient
Sig. (2-tailed) .888 . .000
N144 144 144
Time Correlation -.011 1.000** 1.000
Coefficient
Sig. (2-tailed) .894 .000 .
N144 144 144
**. Correlation is significant at the 0.01 level (2-tailed).
There is a linear relationship between the amount of time spent in prayer and the age at which the
person is spending the most time praying, as seen in the data. Based on the population's existing
culture, the gender of the individual has little bearing on how much time is spent praying each day. It
is understood that those who are younger will spend more time praying because they have the
stamina and mental capacity to do so, as opposed to older people who might not have the same
level of endurance.
144144
N
Reference:
1. The Relationship prayer has on quality of life in later adulthood; Ann RW, Luis EE, Lucas EE.
2. Age Differences in patterns and correlates of the frequency of prayer: Jeffrey SL, Robert JT.
