# STATISTICS: REVISION CARDS

- Created by: rebeccamaria
- Created on: 11-04-15 13:12

## STATISTICS: Types of data

**TYPES OF DATA**

Data can be:

**quantitative -** numerical data e.g. height of people

**qualitatitive -** worded data e.g. colour of hair

There are two types of quantitative data can be:

**discrete** - is data that can be counted/measured exactly e.g. number of pets

**continuous** - can take any value within a range (interval) e.g area, temperature

## STATISTICS: Collecting data

COLLECTING DATA

**Primary data** - data you have colected yourself.

Advantages: you know how and where it was collected / It is more reliable and accurate

Disadvantages: time consuming, expensive.

**Secondary data ****-** data collected by someone else.

Advantages: cheap & easy to obtain.

Disadvantages: might be out of date, have mistakes, don’t know how it was collected.

** **

## STATISTICS: Grouping data

**Grouping data:**

When the spread of data is too big we often group the data in a **frequency table** using **class intervals. **Grouping data can result in loss of accuracy in both calculations & presentations. But it also, makes it easier to analyse!

**Bivariate data:**

Bivariate data are used when you **measure 2 varibles** which are **related things** e.g. height & weight of children.

You can put data onto different scales:

** ** →** Categorical scales:** give **numbers** or **names** to the classes **qualitative data** so they cn be more **easily processed**. The numbers are **only** used for **labelling the classes** - they don't have any other meaning (groups)

** **→ **Ranked scales:** give **numbers** to the classes, so they can be **ordered** into a ** list** (put into order)

## STATISTICS: Census

A census is a **official survey** of **all the members of the population**

1) If you want to carry out a census you need to** carefully define your population**. This means knowing** exactly who is in the population**, so you can be sure you have surveyed everyone.

2)It is easier to to carry out a census on a **small population** because, they are fewer members to survey.

ADVANTAGES

- It helps the government plan for the future
- The data you get will be more accurate
- Shows the government the population status of the country

DISADVANTAGES

- Takes longer to collect, process, and release data than from a sample
- Very expensive to conduct
- Impratical

## STATISTICS: Sampling

When it's not sensible or possible to use a cenus, you have too use sampling.

-Sampling is a **cheap** and **easy alternative** to a census.

SAMPLING - a small appropiate number of people or things to be surveyed

ADVANTAGES

- It is
**quicker, cheaper and****more pratical**than doing a census of an an entire population.

DISADVANTAGES

- You
**don't**have information about**every member**of the population so it can be**less accurate.**

SAMPLE FRAME

Before you choose a sample from a population, you need to make a **list** or **map** of **all the members of the population** - this is called a **sample frame.**

## STATISTICS: Simple random sampling

**Simple random sampling** - is where everything has an equal chance of being chosen e.g. like a lottery

1) In a **simple random sample,** you r**andomly selec**t your dample from the sample frame.

2) It's easy do this sampling with a **small, well defined population.**

3) To select the sample you need to use **random numbers.**

**Here's how you do it:**

** ** Number everything/person, then choose these numbers by placing them in a box and selecting the number randomally.

Advantages: Every member of the population has an equal chance of being selected, so it's completely unbiased.

Disadvantages: It's not always pratical or convenient e.g if the population spread iss over a karge area, the researcher will have to travel a lot.

## STATISTICS: Stratified sampling

**Stratified sampling** is **samples taken** from **every/different catogories.**

1) Sometimes the population might be made is of **groups** or **categories** that contain members which are **similar** to each other in some way e.g. gender or age groups

2) In these cases you can use **stratified sampling** you give the different groups in the sample an amount of **representation** thats **proportional** to how big they are in the population - which means big groups get more representation and small group get less.

3) Then you choose the right number from each group at **random** to make your sample.

**ADVANTAGE:** If you have easy to define catogories in the population (e2.g. males and females) this is likely to give you a representative sample.

**DISADVANTAGE:** It can be **expensive** because, of the extra detail involved.

**Sample size for each layer =**

**Size of whole sample/Size of population × size of layer**

## STATISTICS: Systematic sampling

**Systematic sampling** - is every nth number is taken from the sampling frame

**1)** You can use **systematic sampling** to generate your sample when the population is **very large.**

**2)** It works by choosing a **random starting point** then taking a sample at **regular intervals **afterwards

You need a **well defined population** for **systematic sampling.**

**STEPS**

→First you need o number all the products.

→Next divide your sample frame by sample size

→Then choose a random start number

**ADVANTAGES:** This should produce an unbaised sample and can be carried out by a machine

**DISADVANTAGES:** The nth item might coincide with a pattern which will make it biased

## STATISTICS: Cluster sampling

1) In **larger population,** you can pick out smaller groups called **clusters** - they're oftern **based on criteria** like location e.g. towns within a city.

2) **Cluster sampling** is where random sample of clusters is chosen and then, **every member** in those clusters is included in your sample.

3)The **closer the distribution** of members **within the cluste**r is **to the whole population**, **the less bias** there will be in a study.

4) For this type of sampling you **only** need a lit of the **clusters** and the **members in the sampled clusters.**

ADVANTAGE: It's fairly **convenient**- can **save** a lot of **travel time** when the - population is spread over a l**arge area.**

DISADVANTAGE: It's easy to get a **biased** result e.g. people living in the same street could have **similar incomes** or **employment**

## STATISTICS: Quota sampling

**Quota research** - Is oftern used for **Market Research.**

**1) The population is divided up into groups.**

**2) Then an interviewer is told to interiew a certain number of people from each group.**

**3)** This method of sampling is oftern used in **interviews** carried out on **high streets** and the final choice of the sample members is down to the interviewer - so it is **not random.**

**ADVANTAGE**

**Quick** to use and any member of the sample can be replaced by one with the same characteristics.

**DISADVANTAGE**

It can easily be **biased**, though - the sample chosen **depends on the interviewer. **

## STATISTICS: Convenience sampling

1) The sample is **chosen for ease** and **convenience** so it's **not random**.

2) It's **taken from a section** of the population present at **one particular place and time**.

3) Convenience sampling is easy to do but your **unlikely** to end up with a sample that's **representative** of the population.

ADVANTAGE

-It's easy to take the sample at a **place and time** which **suits** the **interviewer. **

-Don't need a list of the whole population

DISADVANTAGE

-It can be **very biased**

-There's no attempt to make the sample **representative** of the population surveyed.

## STATISTICS: Make sure questions are...

-Not biased

-Not personal

-Include all choice of answers

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