1. Statistics Made Simpleα
By: David Negrelli Σ δ2

2. Introduction
The ability to describe data in various ways has always been important. The need to organize masses of information has led to the development of formalized ways of describing data. The purpose of this presentation is to introduce the reader to basic tenants of statistics.

3. Table Of Contents Frequency distribution Measures of central tendency
Measures of dispersion
Statistical significance
T-test calculations
Degrees of freedom
Levels of significance
Finding the critical value of T
Filling out summary table
Writing the results

4. Frequency Distribution
Data is collected and often organized into formats that are interpreted easily.
Example: Plant height due to the application of fertilizers. Height is given in centimeters (cm.)

5. Frequency Distribution (cont.)
Number of plants 12 12 9 10 11 12 13 8 9 10 11 12 13 14 15
Height (cm)

6. Measures of Central Tendancy
Median- The middle number in a set of data.
Mode- The number within the set of data that
appears the most frequently.
Mean- The average
a. Denoted by х
b. Calculated by the following
formula
Х = Σx n

7. Measures of Dispersion
Variance- Determined by averaging the squared
difference of all the values from the mean.
- symbolized by δ2
δ2 = Σ (х – х)2
n-1

8. Measure of Dispersion (cont.)
Standard Deviation- Is a measure of dispersion that defines how an individual entry differs from the mean.
- calculated by finding the square root of the
variance.
Defines the shape of the normal distribution curve
δ = √ δ2

9. The red area represents the first standard deviant.
68% of the data falls within this area.
Calculated by x ± δ
The green area represents the second standard deviant.
95% of the data falls within the green PLUS the red area.
Calculated by x ± 2δ
The blue area represents the third standard deviant.
99% of the data falls within blue PLUS the green PLUS the red area.
Calculated by x ± 3δ

10. Statistical Significance
Statistical significance is calculated by determining:
if the probability differences between sets of data occurred by chance
or were the result of the experimental treatment.
Two hypotheses need to be formed:
Research hypothesis- the one being tested by the researcher.
Null hypothesis- the one that assumes that any differences within the set of data is due to chance and is not significant.

11. Statistical Significance (cont.)
Example of Null Hypothesis:
The mean weight of college football
players is not significantly different
from professional football players.
µcf = µpf
µ, ‘mu’ symbol for
Null Hypothesis

12. T-Test
Statistical test that helps to show if there is a real difference between different treatments being tested in a controlled scientific trial.
The Student t test is used to determine if the two sets of data from a sample are really different?
The uncorrelated t test is used when no relationship exist between measurements in the two groups.

13. T-Test Calculations (cont.)
Two basic formulas for calculating an uncorrelated t test.
Equal sample size
x1 – x2
t = √
δ21 + δ22 n
Unequal sample size
x1 – x2
t = √
( n1 – 1)δ21 + ( n2 – 1) δ22 ∙
( )
n n2
n1 + n2 – 2

14. Degrees of Freedom
Represents the number of independent observations in a sample.
Is a measure that states the number of variables that can change within a statistical test.
Calculated by n-1 ( sample size – 1)

15. Levels of Significance
Is determined by the researcher.
Symbolized by α
Is affected by the sample size and the nature of the experiment.
Common levels of significance are
.05, .01, .001
Indicates probability that the researcher made an error in rejecting the null hypothesis.

16. Finding the Critical Value of t
A probability table is used
First determine degrees of freedom
Decide the level of significance

17. Critical Value t (cont.)
Example: degrees of freedom= 4
α= .05
The critical value of t= 2.776

18. Critical Value t (cont.)
If the calculated value of t is less than the critical value of t obtained from the table, the null hypothesis is not rejected.
If the calculated value of t is greater than the critical value of t from the table, the null hypothesis is rejected.

19. Filling out Summary Table
The following information is needed in a summary table
Mean
Variance
Standard deviation
1SD (68% Band)
2 SD (95% Band)
3 SD (99% Band)
Number
Results of t test
Descriptive statistics

20. Summary Table (cont.)
Example: Data obtained from a experiment comparing the number of un-popped seeds in popcorn brand A and popcorn brand B.
A B
Is the difference significant?

21. = 23 = 30 Determine mean, variance and standard deviation of samples.
Mean xA
= Σx =
= 23 n 4
Mean xB
= Σx n =
= 30 4

22. Popcorn A = ( 26-23)2 + (22-23)2 + (30-23)2 + (34-23)2
variance
δ2= Σ (х – х)2
n-1
Popcorn A = ( 26-23)2 + (22-23)2 + (30-23)2 + (34-23)2 3 = 3
= 60
Popcorn B = ( 30-30)2+ (35-30)2 + (20- 30)2 + (33- 30)2 3 =
= 44.67 3

23. √ √ δ= √ δ2 Standard deviation: popcorn A Popcorn B 60 = 7.75 44.67
= 6.68

24. √ √ √ = 1.38 Finding Calculated t t = 23 - 30 t = n 60+ 44.67 4 = 7
x1 – x2
t = √
δ21 + δ22 n
t = √ 4 = √
26.17 =
= 1.38
5.12

25. Determine critical value of t
Select level of significance α=.01
Determine degrees of freedom
degrees of freedom of A= 3
degrees of freedom of B= 3
total degrees of freedom = 6
Critical value of t = 3.707
Calculated value of t =1.38 is less than critical value of t from the table,
The null hypothesis is not rejected.

26. Filling the Summary Table
Descriptive statistics popcorn A popcorn B 23 30
Mean
Variance
Standard deviation
1SD (68% Band)
2 SD (95% Band)
3 SD (99% Band)
Number 60
44.67
7.75
6.68 4 4
Results of t test
t= df=6
t of 1.38 < α=.01

27. Writing The Results
Write a topic sentence stating the independent and dependent variables and a reference to a table or graph.
Write sentences comparing the measures of central tendency of the groups.
Write sentences describing the statistical tests, levels of significance, and the null hypothesis.
Write sentences comparing the calculated value with the required statistical value. Make a statement about rejection of the null hypothesis.
Write a sentence stating support of the research hypothesis by the data.