Confidence Interval
The quantitative variable of interest chosen for this discussion
is the continuous variable “Highest Year of school completed”.
This variable has been calculated, measured and analyzed by
using the SPSS as statistical toll to see the trends and the
differences when the confidence interval changes from 90% to
95%, as well as the size of sample change (100 and 400).
Random sample of 100
The confidence interval of the 100 sample of the total
population (2538) responded to this data at:
90% is 13.20 for the
Lower Bound and 14.24 for the upper Bound (figure 2).
95% is 12.83 for the
Lower Bound and 14.11 for the upper Bound (figure 3).
The mean of 100 sample of this variable at 90% of confidence
interval is 13.72 and at the 95% is 13.47.
The standard deviation of this variable at 90% confidence
interval is 3.150, and at 95% of confidence interval is 3.239.
Descriptive Statistics
N
Minimum
Maximum
Mean
Std. Deviation
HIGHEST YEAR OF SCHOOL COMPLETED
100
6
20
13.72
2.854
Valid N (listwise)
100
Figure 1
: Random sample of 100
Descriptives
Statistic
Std. Error
HIGHEST YEAR OF SCHOOL COMPLETED
Mean
13.72
.315
90% Confidence Interval for Mean
Lower Bound
13.20
Upper Bound
14.24
5% Trimmed Mean
13.79
Median
14.00
Variance
9.921
Std. Deviation
3.150
Minimum
2
Maximum
20
Range
18
Interquartile Range
4
Skewness
-.415
.241
Kurtosis
1.376
.478
Figure 2
: 90% confidence interval of 100 random sample.
Descriptives
Statistic
Std. Error
HIGHEST YEAR OF SCHOOL COMPLETED
Mean
13.47
.324
95% Confidence Interval for Mean
Lower Bound
12.83
Upper Bound
14.11
5% Trimmed Mean
13.56
Median
13.00
Variance
10.494
Std. Deviation
3.239
Minimum
3
Maximum
20
Range
17
Interquartile Range
4
Skewness
-.351
.241
Kurtosis
.602
.478
Figure 3
: 95% confidence interval of 100 random sample.
Random sample of 400
The confidence interval of the 400 sample of the total
population (2538) responded to this data at:
90% is
13.58
for the
Lower Bound and 14.08 for the upper Bound (figure 6).
95% is 13.54 for the
Lower Bound and 14.11 for the upper Bound (figure 5).
The mean of 400 sample of this variable at both 90% and 95%
of confidence intervals is 13.83. The standard deviation of this
variable at 90% and 95% of confidence intervals is
2.983
.
Descriptive Statistics
N
Minimum
Maximum
Mean
Std. Deviation
HIGHEST YEAR OF SCHOOL COMPLETED
400
0
20
13.62
3.076
Valid N (listwise)
400
Figure 4:
Random sample of 400
Descriptives
Statistic
Std. Error
HIGHEST YEAR OF SCHOOL COMPLETED
Mean
13.83
.149
95% Confidence Interval for Mean
Lower Bound
13.54
Upper Bound
14.12
5% Trimmed Mean
13.86
Median
14.00
Variance
8.898
Std. Deviation
2.983
Minimum
0
Maximum
20
Range
20
Interquartile Range
4
Skewness
-.382
.122
Kurtosis
1.854
.243
Figure 5
: 95% confidence interval of 400 random sample.
Descriptives
Statistic
Std. Error
HIGHEST YEAR OF SCHOOL COMPLETED
Mean
13.83
.149
90% Confidence Interval for Mean
Lower Bound
13.58
Upper Bound
14.08
5% Trimmed Mean
13.86
Median
14.00
Variance
8.898
Std. Deviation
2.983
Minimum
0
Maximum
20
Range
20
Interquartile Range
4
Skewness
-.382
.122
Kurtosis
1.854
.243
Figure 6
: 90% confidence interval of 400 random sample.
Based on the descriptive statistics of the chosen variable for
this discussion, and all figures presented in this page, the
confidence interval knows some very minimal changes and is
impacted by the size of the sample and the confidence interval
levels (90% and 95%). Also I noticed that the confidence
interval at 95% for upper bound 14.11 remained the same. When
the random sample increased from 100 to 400, the standard
deviation decreased from 3.150 at 90% and 3.239 at 95% to
2.983.
Regarding the statement, “Confidence intervals are
underutilized”, majority of student or professionals do not take
into account the sample size of the population or they misuse it.
Sample size estimation is based on scientific calculation and
confidence level to obtain or achieve a certain level of
confidence and accuracy of the data that represents the reality
or describe the studied subject in a concrete manner. The
implications that may occur when not using the confidence
intervals will be related to validity and reliability of the
research and data presented, witch may raise lot of questions of
the integrity of the researcher.
Note: I am attaching the response for this discussion in word
document in case the table are not shown in this discussion
space.
Reference
Frankfort-Nachmias, C., & Leon-Guerrero, A. (2011). Social
statistics for a diverse society (6
th
ed). Thousand Oaks, CA: Sage Publications.
Wagner, W. E. (2016). Using IBM SPSS Statistics for research
methods and social science statistics (6
th
ed.). Thousand Oaks, CA: Sage Publications.

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Confidence IntervalThe quantitative variable of interest chose.docx

  • 1. Confidence Interval The quantitative variable of interest chosen for this discussion is the continuous variable “Highest Year of school completed”. This variable has been calculated, measured and analyzed by using the SPSS as statistical toll to see the trends and the differences when the confidence interval changes from 90% to 95%, as well as the size of sample change (100 and 400). Random sample of 100 The confidence interval of the 100 sample of the total population (2538) responded to this data at: 90% is 13.20 for the Lower Bound and 14.24 for the upper Bound (figure 2). 95% is 12.83 for the Lower Bound and 14.11 for the upper Bound (figure 3). The mean of 100 sample of this variable at 90% of confidence interval is 13.72 and at the 95% is 13.47. The standard deviation of this variable at 90% confidence interval is 3.150, and at 95% of confidence interval is 3.239. Descriptive Statistics N Minimum Maximum Mean Std. Deviation HIGHEST YEAR OF SCHOOL COMPLETED
  • 2. 100 6 20 13.72 2.854 Valid N (listwise) 100 Figure 1 : Random sample of 100 Descriptives Statistic Std. Error HIGHEST YEAR OF SCHOOL COMPLETED Mean 13.72 .315 90% Confidence Interval for Mean Lower Bound 13.20 Upper Bound 14.24 5% Trimmed Mean 13.79 Median
  • 4. HIGHEST YEAR OF SCHOOL COMPLETED Mean 13.47 .324 95% Confidence Interval for Mean Lower Bound 12.83 Upper Bound 14.11 5% Trimmed Mean 13.56 Median 13.00 Variance 10.494 Std. Deviation 3.239 Minimum 3 Maximum 20 Range 17 Interquartile Range 4 Skewness
  • 5. -.351 .241 Kurtosis .602 .478 Figure 3 : 95% confidence interval of 100 random sample. Random sample of 400 The confidence interval of the 400 sample of the total population (2538) responded to this data at: 90% is 13.58 for the Lower Bound and 14.08 for the upper Bound (figure 6). 95% is 13.54 for the Lower Bound and 14.11 for the upper Bound (figure 5). The mean of 400 sample of this variable at both 90% and 95% of confidence intervals is 13.83. The standard deviation of this variable at 90% and 95% of confidence intervals is 2.983 . Descriptive Statistics N Minimum Maximum Mean Std. Deviation
  • 6. HIGHEST YEAR OF SCHOOL COMPLETED 400 0 20 13.62 3.076 Valid N (listwise) 400 Figure 4: Random sample of 400 Descriptives Statistic Std. Error HIGHEST YEAR OF SCHOOL COMPLETED Mean 13.83 .149 95% Confidence Interval for Mean Lower Bound 13.54 Upper Bound 14.12 5% Trimmed Mean 13.86 Median
  • 8. HIGHEST YEAR OF SCHOOL COMPLETED Mean 13.83 .149 90% Confidence Interval for Mean Lower Bound 13.58 Upper Bound 14.08 5% Trimmed Mean 13.86 Median 14.00 Variance 8.898 Std. Deviation 2.983 Minimum 0 Maximum 20 Range 20 Interquartile Range 4 Skewness
  • 9. -.382 .122 Kurtosis 1.854 .243 Figure 6 : 90% confidence interval of 400 random sample. Based on the descriptive statistics of the chosen variable for this discussion, and all figures presented in this page, the confidence interval knows some very minimal changes and is impacted by the size of the sample and the confidence interval levels (90% and 95%). Also I noticed that the confidence interval at 95% for upper bound 14.11 remained the same. When the random sample increased from 100 to 400, the standard deviation decreased from 3.150 at 90% and 3.239 at 95% to 2.983. Regarding the statement, “Confidence intervals are underutilized”, majority of student or professionals do not take into account the sample size of the population or they misuse it. Sample size estimation is based on scientific calculation and confidence level to obtain or achieve a certain level of confidence and accuracy of the data that represents the reality or describe the studied subject in a concrete manner. The implications that may occur when not using the confidence intervals will be related to validity and reliability of the research and data presented, witch may raise lot of questions of the integrity of the researcher. Note: I am attaching the response for this discussion in word document in case the table are not shown in this discussion space. Reference
  • 10. Frankfort-Nachmias, C., & Leon-Guerrero, A. (2011). Social statistics for a diverse society (6 th ed). Thousand Oaks, CA: Sage Publications. Wagner, W. E. (2016). Using IBM SPSS Statistics for research methods and social science statistics (6 th ed.). Thousand Oaks, CA: Sage Publications.