# Collective Data and Presentation

Topics: Sampling, Stratified sampling, Cluster sampling Pages: 5 (1278 words) Published: September 27, 2013
MATH TOPICS

CHAPTER 2
DATA COLLECTION AND PRESENTATION
2.1 Data Collection
This section aims to:
1. Identify, compare and contrast the different types of data; 2. List and explain the various techniques of selecting a sample; and 3. Enumerate and illustrate the different sampling techniques Types of Data

Data is a collection of facts, such as values or measurements. It can be numbers, words, measurements, observations or even just descriptions of things. Two types of Data
Primary Data means original data that has been collected specially for the purpose in mind. It means someone collected the data from the original source first hand. Data collected this way is called primary data Data Collected Through Personal Investigation:

This data is collected by the investigator or the researcher or the researching team personally. The researcher or the team of researchers collects this data through the surveys that they conduct themselves. This type of data is more accurate as it is collected directly by the researcher. Data Collected Through Workers:

The researcher or the researching team may hire another person or a group of people for conducting a survey to collect a data. Secondary data is data that has been collected for another purpose. When we use Statistical Method with Primary Data from another purpose for our purpose we refer to it as Secondary Data. It means that one purpose's Primary Data is another purpose's Secondary Data. Secondary data is data that is being reused. Usually in a different context.

Sampling Techniques
Sampling is a fundamental aspect of statistics, but unlike the other methods of data collection, sampling involves choosing a method of sampling which further influences the data that you will result with. There are two major categories in sampling: probability and non-probability sampling. Two types of Sampling techniques

Probability Sampling
Under probability sampling, for a given population, each element of that population has a chance of being picked to part of the sample. In other words, no single element of the population has a zero chance of being picked The odd/chances/probability of picking any element is known or can be calculated. This is possible if we know the total number in the entire population such that we are then able to determine that odds of picking any one element. Probability sampling involves random picking of elements from a population, and that is the reason as to why no element has a zero chance of being picked to be part of a sample. Non-Probability Sampling

Unlike probability sampling, under non-probability sampling certain elements of the population might have a zero chance of being picked. This is because we can't accurately determine the chances/probability of picking a given element so we do not know whether the odds of picking that element are zero or greater than zero. Non-probability sampling may not always be a consequence of the sampler's ignorance of the total number of elements in the population but may be a result of the sampler's bias in the way he chooses the sample by excluding some elements. EXERCISES

Classify each variable as discrete or continuous
1. The heights of pupils in class 3A.
2. he number of chocolates in various 500g boxes.
3. The times taken for athletes to run 100m
4. Speed of the train
5. Time to wake up in the morning
Methods of Probability Sampling
There are a number of different methods of probability sampling including: Random Sampling
1. Random sampling is the method that most closely defines probability sampling. Each element of the sample is picked at random from the given population such that the probability of picking that element can be calculated by simply dividing the frequency of the element by the total number of elements in the population. In this method, all elements are equally likely to be picked if they have the same frequency. Examples

1. In a medical...

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