This document discusses statistical concepts like mean, standard deviation, coefficient of variation, standard error, and p-value. It provides examples to calculate these values from a dataset of restaurant receipts. The mean was calculated as $49.2, the standard deviation as $17, and the coefficient of variation as 34.6%. A hypothesis test was conducted to determine if the proportion of people in a city that can speak more than one language is higher than the national average of 26%. The p-value was calculated to be 0.0336, which fails to reject the null hypothesis that the proportion is equal to 26%.

1. Name- SARAF PRIYA MADHAV
FINAL YEAR B.PHARMACY SEMESTER VIII
EXPERIMENT OF BIOSTATISTICS WITH
EXAMPLE

2. AIM- To determine and explain the mean ,standard
deviation, coefficient variance,standard error and p value

3. Formula-
MEAN:-
 The MEAN is the numerical average of the data set.The mean is
found by adding all the values in the set, then dividing the sum
by the number of values.
STANDARD DEVIATION-
 Standard Deviation shows the variation in data. If the data is
close together, the standard deviation will be small. If the data is
spread out, the standard deviation will be large.

4. coefficient of variation -
 (CV) is the ratio of the standard deviation to the mean. The higher
the coefficient of variation, the greater the level of dispersion around
the mean. It is generally expressed as a percentage ...It is also called as
relative deviation(RSD)
 Standard error of(mean)
The term "standard error" is used to refer to the standard deviation of various
sample statistics, such as the mean or median

5. Exercise :-example
The owner of the john Taye restaurant
is interested in how much people
spend at the restaurant.
He examines 10 randomly selected
receipts for parties of four and writes
down the following data.
44, 50, 38, 96, 42, 47, 40, 39, 4
6, 50

6. calculations
This tells us that the standard deviation of the restaurant
bills is 34.6% of the mean.

7. • The p-value is the probability of obtaining results at least as extreme as the
observed results of a statistical hypothesis test, assuming that the null hypothesis is
correct. ... A smaller p-value means that there is stronger evidence in favor of the
alternative hypothesis
• Being a probability, P can take any value between 0 and 1. Values close to 0 indicate
that the observed difference is unlikely to be due to chance, whereas a P value
close to 1 suggests no difference between the groups other than due to chance.
P VALUE ( probability value)

8. Q.Fay read an article that said 26% of Americans can speak more than one
language. She was curious if this figure was higher in her city, so she tested Ho
: p = 0.26 vs. Ha : p > 0.26, where p represents the proportion of people in her
city that can speak more than one language.
She found that 40 of 120 people sampled could speak more than one
language. The test statistic for these results was z 1.83.
Assuming that the necessary conditions are met, what is the approximate P-
value for Fay's test?
P- value Problem

9. NULL HYPOTHESIS
.
Therefore,
P- value =0.0336 > 0.05
Therefore, from the conclusion, if
p>0.05, the null hypothesis is
accepted or fails to reject.
Hence, the conclusion is “fails to
reject H0.”
P value determination

10. RESULT-
To determination the mean ,standard deviation, coefficient
variance, standard error and p value was done successfully.
PARAMETER RESULT
Mean 49.2
Standard deviation 17
Coefficient variance 34.6%
Standard error 3.4
P value 0.0336>0..05

11. Conclusion-
• Statistical analysis plan should be devised before collecting data. • Use aims of study
to decide the best way to study the relationship between variables of interest —
correlations, hypothesis testing, modeling.
• Identify and develop treatments for disease and estimate their effects. Identify risk
factors for diseases. Design, monitor, analyze, interpret, and report results of clinical
studies. Develop statistical methodologies to address questions arising from
medical/public health data. Locate ,
• The p-value is used as an alternative to rejection points to provide the smallest level of
significance at which the null hypothesis would be rejected. A smaller p-value means that
there is stronger evidence in favor of the alternative hypothesis.