In: Math
total, 16 patients were enrolled in the study. Values of the f-wave frequency during day- and night-time are given in the table below.
| 
 Time of the day  | 
 Aggregation values  | 
|||||||||||||||
| 
 Day-time (n = 16)  | 
 6.23  | 
 6.91  | 
 6.35  | 
 6.29  | 
 6.45  | 
 6.30  | 
 6.60  | 
 6.54  | 
 6.64  | 
 6.90  | 
 6.11  | 
 7.28  | 
 6.93  | 
 7.89  | 
 7.21  | 
 6.90  | 
| 
 Night-time (n = 16)  | 
 6.41  | 
 5.98  | 
 6.25  | 
 6.03  | 
 6.57  | 
 6.25  | 
 6.51  | 
 6.50  | 
 6.50  | 
 6.41  | 
 6.70  | 
 6.03  | 
 6.60  | 
 6.77  | 
 6.88  | 
 6.93  | 
Data analysis.
(decide which sampling technique was used to collect the data;
check if the data is normally distributed and if the variances of the groups are similar;
present data graphically; briefly interpret the results)
Sampling technique: The data is probably an average for multiple readings (say 4 or 5 readings) for each of the 16 patients during day time and during night time. Taking multiple readings would reduce errors and get a closer to true value for each patient.
Below is the data summary:
| 
 Time of the day  | 
Average | Std Dev | Median | Minimum | Maximum | 
| Day-time (n = 16) | 6.720625 | 0.469332 | 6.62 | 6.11 | 7.89 | 
| Night-time (n = 16) | 6.4575 | 0.292313 | 6.5 | 5.98 | 6.93 | 
Both mean and median are greater for Day-time and less for Night-time data. The Minimum and Maximum are also greater. In 12 out of 16 patients, that is 75% cases, the Day-time frequency is greater than Night-time frequency.
Below is the histogram and QQ-plots vs. normal distribution. The distribution are close but not normal. The first is skewed to right and second shows slight left skew with a much higher mode.




Comparison of Variances:
Standard Error for Day-Time = 0.469332
Standard Error for Night-time = 0.292313
Standard Error is an estimate for square root of Variance.
Therefore Day-time has greater variance. Test of Hypothesis for equality of two variances is the F-test.
The Test Statistic is
F = Var(1) / Var(2)
where Var(1) and Var(2) are the sample variances in groups 1 and 2.
The degrees of freedom for F are N_1 - 1 and N_2-1 where N_1 and N_2 are sample sizes of groups 1 and 2.
Null Hypothesis is that Day-time variance = Night-time variance
Alternative Hypothesis for 1-tailed is that Day-time variance is greater.
F statistic for the given data is
F = (0.469332*0.469332) / (0.292313*0.292313)
F (df1 = 15, df2 = 15) = 2.577899
With alpha = 0.05 for a 1-tailed distribution
check if F is greater than the critical value.
F_critical_upper_limit = 2.40
Reject null hypothesis of equality of variances if F > 2.40
F-value = 2.577899
We can reject the null hypothesis at significance level alpha = 0.05 and accept alternative hypothesis that the Day-Time observations show greater variance. This is also clear from the histograms, because the Day-time data shows greater spread (range for day-time = 1.78 vs. range for night-time = 0.95), whereas Night-time shows a sharp mode and is centered around the mode.