Research Design and Implemenation





Aims and Hypothesis


An Aim should be the starting point of any investigation, in order to successfully create an aim the researcher must fully understand the intended purpose of the study.

Alternate Hypothesis predicts that something other than chance alone has played a part in producing the results obtained.

Directional Hypothesis this type of hypothesis is one which predicts the direction of the difference or in terms of correlational analysis predicts either a positive or negative correlation.    A directional hypothesis is also called a one tailed hypothesis. 


A Non Directional Hypothesis on the other hand predicts a difference between two variables but not the direction or in terms of correlational analysis it does not predict either a positive or negative correlation.   A non directional hypothesis is also called a two tailed hypothesis.

Null Hypothesis predicts that the results obtained from an investigation are due to chance alone. For example in an experiment investigating the use of mnemonics and memory recall, a null hypothesis would be that the use of mnemonics would have no effect on memory recall. If any differences do occur they are solely due to chance and nothing else. The researchers task is to decide after they have obtained their findings whether the null hypothesis should be accepted or rejected. The null hypothesis if accepted causes the alternative hypothesis to be rejected.















Quota Sampling A quota sample is an attempt to make a sample representative by having the same proportions of different groups of people in the sample and in the population.

When you cannot take a random sample of the population, but you want to make your sample as representative as possible on a small number of variables, a quota sample can be used. You may know the proportions of people of different ages, salaries and sex in the population of interest. To make your sample to be as representative as possible, you want to reflect the proportions of the characteristics in the sample population.

Random sampling A random sample is a sample in which every member of the population has an equal chance of being selected and that selection of one member of the population does not alter the chances of any other person being selected

It is the best method of selecting your sample from the population of interest. It is also the most difficult to achieve. Strictly speaking, statistical analyses are only valid if random samples are drawn. However non-random samples, as long as they are not biased in any way can be a reasonable alternative.

True random sampling is very rare, a perfection which can never be quite achieved. If someone says that taken a random sample your first instinct should be not to believe them. If you write in a report that you took a random sample, you almost certainly did not. The ONLY way to get a random sample




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