Neural Differentiation of iPSCs: Summary Statistics, ANOVA and T-Test Results

Neural differentiation of iPSCs 1
EXPERIMENT: NEURAL DIFFERENTIATION OF IPSCS
By (Name)
The Name of the Class (Course)
Professor (Tutor)
The Name of the School (University)
The City and State where it is located
The Date

Neural differentiation of iPSCs 2
Experiment: Neural differentiation of iPSCs
Question 1
We are going to use Microsoft Excel to generate summary statistics that will aid in the
description of the data collected from the 6 individuals. The summary statistics will comprise of
measures of central tendency and dispersion. The summary results for SOXI/GAPDH and
NANOQ/GAPDH will be represented separately. The following results were generated for
summary statistics
Results for SOXI/GAPDH
Control X Y Z
Mean 0.10 Mean 13.28 Mean 1.95 Mean 17.10
Standard
Error
0.02 Standard
Error
5.28 Standard
Error
1.17 Standard
Error
6.97
Median 0.11 Median 7.85 Median 0.73 Median 8.00
Mode #N/A Mode #N/A Mode #N/A Mode #N/A
Standard
Deviation
0.04 Standard
Deviation
12.93 Standard
Deviation
2.86 Standard
Deviation
17.08
Sample
Variance
0.00 Sample
Variance
167.17 Sample
Variance
8.17 Sample
Variance
291.78
Kurtosis -1.33 Kurtosis 0.87 Kurtosis 4.00 Kurtosis 0.88
Skewness -0.36 Skewness 1.28 Skewness 1.99 Skewness 1.42
Range 0.11 Range 34.60 Range 7.43 Range 42.40
Minimum 0.04 Minimum 1.10 Minimum 0.07 Minimum 4.60
Maximum 0.15 Maximum 35.70 Maximum 7.50 Maximum 47.00
Sum 0.61 Sum 79.70 Sum 11.69 Sum 102.60
Count 6.00 Count 6.00 Count 6.00 Count 6.00
Results for NANOQ/GAPDH
Control X Y Z
Mean 28.60 Mean 27.20 Mean 2.52 Mean 0.48
Standard
Error
9.62 Standard
Error
9.71 Standard
Error
2.20 Standard
Error
0.26
Median 22.00 Median 20.00 Median 0.39 Median 0.28

Neural differentiation of iPSCs 3
Mode #N/A Mode #N/A Mode 0.13 Mode #N/A
Standard
Deviation
23.55 Standard
Deviation
23.79 Standard
Deviation
5.38 Standard
Deviation
0.65
Sample
Variance
554.75 Sample
Variance
566.04 Sample
Variance
28.98 Sample
Variance
0.42
Kurtosis 4.63 Kurtosis 4.96 Kurtosis 5.98 Kurtosis 4.30
Skewness 2.08 Skewness 2.17 Skewness 2.44 Skewness 2.01
Range 63.80 Range 64.10 Range 13.37 Range 1.73
Minimum 11.20 Minimum 10.40 Minimum 0.13 Minimum 0.02
Maximum 75.00 Maximum 74.50 Maximum 13.50 Maximum 1.75
Sum 171.60 Sum 163.20 Sum 15.10 Sum 2.90
Count 6.00 Count 6.00 Count 6.00 Count 6.00
It is clear that all data samples regardless of treat are skewed either to the left or the right.
Nevertheless, the control measure for SOXI expression is almost symmetrical because the mean
and median are almost the same. The treats (X, Y, and Z) and control for SOXI do not have the
same mean; similarly, the means for treats and control in NANOQ are all different.
Question 2
Statistical tests can be performed on the data to evaluate different hypotheses. For example, we
can perform hypotheses test to assess whether the differences among the means for X, Y, & Z
are significant at an alpha=0.05. We will perform two ANOVA tests and two t-tests for SOXI
and NANOQ data. We results for ANOVA: single factor analysis in excel are presented below.
Where the hypothesis being tested is:
Null hypothesis: The mean for the three treatments X, Y, and Z are the same
Alternative hypothesis: There is significant difference in the means for at-least one of the
treatments
ANOVA for SOXI
Anova: Single Factor
SUMMARY