Biostat

Front 1

Definition

Back 1

Statistics - collection , classification, analysis and interpretation of numerical data (Coxten and Cowden)

Front 2

Principles of Biostatistic

Back 2

1. Collection of data

2. Organisation of data

3. Presentation of data

4. Analysis of data

5. Interpretation of data

Basis for statistical analysis

1. The population (U)

2. The set of characteristics (variables) of the units of this population (V)

3. The probability distribution (P) of these characteristics in the population.

Front 3

Measures of Central tendency- definition

Back 3

The value around which the other values are distributed.

Front 4

Measures of Central tendency- Objectives

Back 4

Condense entire mass of data and to facilitate comparison

Front 5

Measures of Central tendency- Ideal properties

Back 5

1. It should be easy to understand and compute.

2. It should be based on each and every item in the series.

3. It should not be affected be extreme observations (either too small or too large)

4. It should have sampling stability

Front 6

Measures of Central tendencies- types

Back 6

1. Arithmetic mean (mathematical estimate)

2. Median (positional estimate)

3. Mode (based on frequency)

Front 7

Arithmetic mean

Back 7

1. Simplest measure of Central tendency.

2. You can give examples😏

Advantage-

1. Easy to calculate and understand

2. It is the most useful of all the averages.

Disadvantages-

1. May be unduly influenced by abnormal values.

2. Sometimes it may look ridiculous.

Front 8

Median

Back 8

Middle value in the distribution such that

One half have a smaller or equal value as of median and

Other half have a larger or equal value as of median.

1. Arrange the data in ascending or descending order

2. Apply the formula .

Advantage

Not affected by the abnormal values

Disadvantages

No further analysis can be obtained

For eg . If we have median of 2 groups. We can't get combined median of the 2.

Front 9

Mode

Back 9

The value in series of observations that has maximum repetition (frequency)

1. Look for highest frequency observation. Or

2. Apply formula

3 median - 2 mean

Advantage-

1. Not affected by the abnormal values

2. Easy to calculate

3. Can be calculated in qualitative data.

Disadvantages-

1. Can't be used for further analysis

2. There can be multiple or no modal value for a particular set of observations.

3. Less common.

Front 10

Measures of Dispersion

Back 10

Dispersion - the degree of spread or variation of a variable about a central value.

The common measures of dispersion are-

1. Range

2. Mean deviation

3. Standard deviation

Front 11

Range

Back 11

Difference between highest and lowest observations.

Advantage-

1. Simple to calculate.

Disadvantages-

1. No info about values that lie between the extreme values

2. Subject to fluctuation from sample to sample.

Front 12

Mean deviation

Back 12

Average of deviations from arithmetic mean.

Advantage-

1. Simple to understand

2. Easy to calculate

3. Takes all observations in consideration.

4. Values of extremes have a little effect on mean deviation.

Disadvantages-

1. Not capable of further analysis and treatment.

2. More accurate when measured from median values (which in themselves are not reliable in a data with varieties of observations)

Front 13

Standard deviation

Back 13

A.k.a.

Root mean square deviation

The square root of mean of squared deviations from arithmetic mean

Greater the standard deviation, greater will be magnitude of dispersion for a given set of data.

Advantage -

1. It is a sensitive measure of dispersion.

2. Takes all observations in consideration.

3. Greater precision.

Disadvantages-

1. Not that easy to calculate.

Front 14

Presentation of data

Back 14

2 methods-

1. Tables

2. Charts and diagrams

Front 15

Bar Charts

Back 15

Method of data presentation by the length of a bar.

Width if bar remain same

Only the length varies.

Bar is separated by spaces.

Can be

1. Horizontal or vertical

2. Simple, Multiple, Component (proportional).

Front 16

Types of data

Back 16

Nature of the data

1. Qualitative

2. Quantitative

A) Discrete

B) continuous

Data collection

1. Primary

2. Secondary

Front 17

Primary data

Back 17

Obtained by investigator himself

It is first hand information.

Methods of primary data collection-

1. Direct personal interview .

2. Oral health examination .

3. Questionnaire method.

Write details, advantages and disadvantages.

Front 18

The normal curve

Back 18

A.k.a. normal distribution, Gaussian distribution.

When data is collected from a large no. of people and

a frequency distribution is made with narrow class interval ,

The resulting curve is smooth and symmetrical

K/a NORMAL CURVE.

Front 19

The normal curve- properties

Back 19

The limits on either side of mean are called confidence limits

1. The area between one SD on the either sides of the mean include 68.3% of values.

2. The area between two SD on either side of mean include 95.4% of values.

3. The area between three SD on either side of mean include 99.7% values.

Front 20

The standard normal curve

Back 20

There are many normal curves for a given set of data but there is only 1 standard normal curve.

1. Bell shaped.

2. Perfectly smooth

3. Based on an infinite no. of observations.

4. Measure of Central tendencies (mean median mode ) coincide.

5. Area of curve= 1

6. Mean = 0

7. SD = 1

Front 21

Chi Square Test- scientist

Back 21

Karl Pearson

Front 22

Chi Square Test- Indications

Back 22

1. Data is measured in terms of attributes or qualities

2. Data is intended to test whether this difference in the distribution of attributes in different groups is due to sampling variation or not

Front 23

Chi Square Test- Uses

Back 23

Test the significance of difference between two proportions and

can be used when there are more than two groups to be compared.

Front 24

Chi Square Test- Steps

Back 24

See last pages of CD notebook

Front 25

Correlation coefficient "r"

Back 25

Correlation between two variables

r= -1 to +1

0 means no correlation

-1 means negative correlation

+1 means positive correlation

Front 26

Father of health statistics

Back 26

John Graunt

Front 27

Types of scales in statistics

Back 27

Nominal- info divided into some definitive quality basis

Eg. Male/female, white/black

Ordinal- rank order

Interval - scale graded in equal increments.

0 doesn't mean absence of character

Eg. Temperature

Ratio scale- has absolute zero

Eg. Ht , wt

Front 28

Sampling methods

Back 28

1. Non Probability

- quota

- purposive (subset- snowball or chain referral)

- convenience

2. Probability

- simple random (lottery, table of random no.)

- systematic

- stratified

#str. Random,

#str. Systemic

- cluster

3. Other

- multiphase

- multistage

Front 29

Coefficient of variance

Back 29