Question

  

Q30.Define the following: 1. Biostatisticsand it is role in public health - When the data analyzed are derived from the biological science and medicine, 2. Statistics - Statistics is a field of study concerned with 1- collection, organization, summarization and analysis of data. 2- drawing of inferences about a body of data when only a part of the data is observed. 3. Sources of Data- Primary sources are original materials, Secondary sources are those that describe or analyze primary sources, Tertiary sources are those used to organize and locate secondary and primary sources. 4. Population and sample- A population: It is the largest collection of values of a random variable for which we have an interest at a particular time. * A sample: It is a part of a population. 5. Outcome and exposure variables. The exposure variable is the variable that you predict will have an effect on the outcome variable, so, you will alter the exposure variable to measure what changes occur in the outcome variable. 6. Types of statistics- descriptive statistics and inferential statistics. 7. Descriptive statistical - are used to synopsize data from a sample exercising the mean or standard deviation. 8. Inferential statistical- are used when data is viewed as a subclass of a specific population. 9. Z score and its importance in normal distribution. The random variable of a standard normal distribution is known as standard score or a Z-score. It is possible to transform every normal random variable X into a z score

Answer 1

1. Biostatistics and it’s role in public health:

Biostatistics is the application of statistics in biology. It analyzes the data relating to botany, zoology and medicine. It plays a significant role in analyzing public health issues such as general diseases and epidemics.

2. Statistics:

In singular sense, statistics is defined as a scientific method employed to i. collect data ii. organize, arrange and present the data systematically iii. analyze the data and iv. correctly interpret the results of analysis which leads to infer on some important characteristics of the data relating to a problem. It is a science of averages and counting.

In plural sense, statistics is simply defined as numerical data relating to quantitative and qualitative characteristics with a view to having statistical analysis.

3. Sources of data:

There are different sources of data such as primary, secondary and tertiary sources. Primary source is the data originally collected by an investigator for a specific purpose. Secondary source is the data collected by some authenticated authority after which the investigator analyzes the collected data. Tertiary sources help us in organizing and locating both primary and secondary sources.

4. Population and sample:

A population is an aggregate of objects or units under statistical enquiry with respect to one or more characteristics. It is also known as an universal set. A sample is a partial collection of some selected objects or units of the population with a view to represent all characteristics of the population. It is a small part of the population and it is known as a non-empty finite sub set of the population.

5. Outcome and exposure variables:

The variable which influences the other variable is called exposure variable and the variable which is influenced by the other variable is called outcome variable. For example between sun light and radiation, sun light is exposure variable and radiation is the outcome variable. Similarly between price and demand of different commodities under normal situations, price is the exposure variable and demand is the outcome variable.

6. Types of statistics:

Mainly there are two types of statistics. Descriptive statistics mainly which deals with calculation of all averages and Inferential statistics mainly which deals with drawing valid conclusions about populations using samples.

7. Descriptive statistics:

Descriptive statistics is concerned with calculation of all statistical measures or averages such as mean, median, mode, range, quartiles, quartile deviation, mean deviation, standard deviation, coefficient of variations, coefficients of skewness, kurtosis etc.

8. Inferential statistics:

Inferential statistics is concerned with various sampling methods to draw samples from populations, estimation of parameters, testing the hypothetical values of parameters and finding confidence intervals for parameters.

9. Z score and its importance in normal distribution:

If a random variable X follows normal distribution with mean M and Variance S^2, then Z= (X-M)/S is the Z score of X follows standard normal distribution with mean 0 and variance 1. It is also called standard normal variable. It is very important transformation in normal distribution and makes easier all calculations in normal distribution. Suppose if we want to find the area of X from a to b then it is equal to find the area of Z from (a-M)/S to (b-M)/S.