BSTAT

1. To Be Able To Effectively Conduct Research

2. To Be Able To Read Journals

3. To Further Develop Critical And Analytic Thinking Skills.

4. To Be An Informed Consumer

5. To Know When You Need To Hire A Statistician

5 PRIMARY REASONS to study statistics CRDIW

To Be Able To Effectively Conduct Research

Statistics provides us with a tool with which to make an educated decision. — know what statistics YOU want to use before YOU collect YOUR data.

to be able to read journals

The ability to extract meaning from journal articles and the ability to critically evaluate research from a statistical perspective are fundamental skills that will enhance your knowledge and understanding in related coursework

statistics

A branch of science which deals with the collection, presentation, analysis, and interpretation of data.

statistics

Numerical characteristics calculated for a set of data (e.g., mean, median, mode)

The backbone of Research

descriptive

inferential

2 branches of statistics

descriptive statistics

• deals with organizing and summarizing observations so that they are easier to comprehend

• used to describe the basic features of the data in a study

• provide simple summaries about the sample and the measures

inferential statistics

- deals with the formulation of inferences about conditions that exist in a population from study of a sample drawn from a population.

- make inferences from the data to more general conditions

population

• all subjects under investigation

• the set of all elements of interest in a particular study

sample

Is a subset of a population.

variable

measurable characteristic of the subject that can take on different values

data

values that the variables can assume

data set

collection of data values

random sample

is a sample selected in such a manner that each element of the population is given an equal chance of being chosen.

qualitative statistics

Also called: Categorical data

• These are non-numerical data used to describe qualities or categories.

• They answer questions like "What kind?", "Which category?", or "Who?"

1. SEX (male or female)

2. COLOR (red, white, blue, etc...)

3. STUDENT CLASSIFICATION BY YEAR LEVEL (freshmen, sophomore, junior, senior)

4. RELIGION (Catholic, Protestant, INC)

5. OCCUPATION (businessman, doctor, lawyer, teacher)

6. LEVEL OF PERFORMANCE ON A JOB ( outstanding. very satisfactory, satisfactory, poor)

7. DATE OF BIRTH

8. CODE NUMBER, ZIP CODE, TELEPHONE NUMBER

EXAMPLES OF QUALITATIVE VARIABLES:

quantitative statistics

Also called: Numerical data

• These are measurable, countable data that involve numbers.

• They answer questions like "How many?", "How much?", or "What is the value?"

variable

are characteristics, numbers, or quantities that can be measured or counted

variable

may also be called a data item

variable

contains a value or description of what is being studied in the sample or population.

Discrete

Continuous

Types under Quantitative Variables

discrete variable

Can take specific, separate values (usually whole numbers)

continuous variable

variables whose values are obtained through the process of measuring and can assume any value within a specified interval or range.

1. AGE

2. MONTHLY INCOME

3. SIZE OF FAMILY

4. HOURLY OUTPUT OF A MACHINE

5. LENGTH OF SERVICE

6. HEIGHT IN CM

7. GRADE IN MATH

examples of quantitative variables

central tendency

general characteristic of the group

scale

way of categorizing data

• nominal

• ordinal

• interval

• ratio

4 Types of Data Measurement Scales

nominal scale

They have no natural order.

Categories are mutually exclusive.

The only number we can calculate for these variables are counts.

The only measure of central tendency we can calculate for these variables is the mode.

ordinal scale

A scale used to label variables that have a natural order, but no quantifiable difference between values.

ordinal scale

data is often collected by companies through surveys who are looking for feedback, about their product or service

interval scale

A scale used to label variables that have a natural order and a quantifiable difference between values, but no "true zero" value

Ratio scale

A scale used to label variables that have a natural order, a quantifiable difference between values, and a "true zero" value.