My Biostatistics Notes

CHAPTER 1 INTRODUCTION TO STATISTICS

OBJECTIVE

 Students should be able to:

1. Determine the difference between descriptive and inferential statistics.

2. Know the statistical terms.

 3. Identify a data type and differentiate between discrete variable and continuous variable.

 4. Differentiate between population and sample data

1.0 Introduction

Statistics is an important field which has been used widely in research of social science, physics, biology, engineering, medicine and business.

Activities involve in Statistics are collecting, organizing, summarizing, presenting and analysing a set of data. Besides that, activities also include drawing valid conclusion and making reasonable decision from the analysed data.

Definition of statistics:

Statistics is defined as a group of methods: collecting, organizing, presenting, analyzing, and interpreting data in order to make decision.

1.1 Types of Statistics

There are two types of statistics, namely:

a. descriptive statistics

b. inferential statistics

Descriptive statistics

Collection, organization, summarization, and presentation of data.

For example, a set of data for the number of students sat for an Statistics examination can be represented in the form of chart or graph for descriptive statistics.

Inferential statistics

Collection of methods that use sample results to come out with decisions or prediction about a population.

1.2 Statistical Terms

1.2.1 Population

Population consists of all elements or objects of the target group whose characteristics are being studied.

Examples: Weight of all students in Statistics class. Name of every students in UNISEL. The total items in a factory.

1.2.2 Sample

Subset or part of a population which has been selected.

Examples: Weight of 50 students in Statistics class. Name of 10 boys in UNISEL.

1.2.3 Random Sample

A random sample is a sample of data which is simply taken from the population.

1.2.4 Survey

The collection of information from the elements of a population or sample.

1.2.5 Census

A survey that includes every element of the target population.

1.2.6 Element

Element is a specific subject or object about which the information is collected.

1.2.7 Data Set

Data set is a collection of observations on one or more variables.

1.2.8 Raw Data

Raw data is the information collected in the original form.

1.3 Types of variable

Variables

Variable is the characteristic that being studied which assumes some values for each element. (Usually random variable is denoted with capital X or capital Y and the value of variable is denoted with lower case x or y)

There two type Variable: Qualitative Variable and Quantitative Variable.

i. Qualitative Variables

Variable cannot be measured numerically. (The value of variable is not in terms of number)

Example – colour of cars, name, student’s grade, blood type.

 Types of food.

ii. Quantitative Variables -

Variable that can be measured numerically.(The value of variable is in terms of number) There two types of quantitative variable: discrete and continuous variable.

 Discrete Quantitative Variables

Measurement values which should take exact value, (The value of variables are countable number) for examples number of students, number of books, number of computers.

 Continuous Quantitative Variables

Variables that can assume all values within a certain interval or more intervals. (The numbers are very close to each other so the values are continuous) For examples height of students, temperature of 50 rooms, weight of sugar, time taken to finish a test and duration of sleep.

FORMULA AND TABLE