CHAPTER 5 CONSTRUCTING HYPOTHESeS

What is A Hypothesis?

•A proposition, condition, or principle which is assumed, perhaps without belief, in order to draw out its logical consequences, and to test its accord (agreement) with facts which are known or may be determined.

What is A Hypothesis?

•A proposition that is stated in a testable form and that predicts a particular relationship between two or more variables (Bailey, 1978: 35).

•A hypothesis is written in such a way that can be proven or disproven by valid and reliable data (Grinnell & Stothers).

From the above definitions, it is apparent that a hypothesis:

1. Is a tentative(experimental) proposition 2. Its validity (rightness) is unknown 3. In most cases, it specifies a relationship

between two or more variables.

Functions of Hypothesis

• Brings clarity, specificity and focus to a research problem, but are not essential.

• Tells you what specific aspects of a research problem to investigate

• Tells you what data to collect and what not to collect

• Enhances objectivity in a study • Enables you to add to the formulation of theory.

It enables you to specifically conclude what is true or what is false.

Characteristics of Hypothesis

1. Should be simple, specific and conceptually clear . Example: The average age of the male staff in this

university is higher than that of the female staff.

The average smokers of the male drivers in this country is higher than that of the female drivers.

There will be no difference in the level of information literacy among university students

Characteristics…(cont.)

2. Should be verifiable.3. Should be related to the existing body of

knowledge.4. Can be put into operation.

Types of Hypothesis 1. Research hypothesis : is any assumption that you seek to validate through an

inquiry.

Example : There will be a significant difference in the TOEFL examination results among students of different programs.

2. Alternate hypothesis : Its main function is to explicitly specify the relationship that

will be considered as true in case the research hypothesis proves to be wrong.

Types of Research Hypothesis

1. Null hypothesis: a statement specifying that there is no

difference between two situations, groups, outcomes, or the prevalence of a condition or phenomenon. It always includes equal sign.=Example: There will be no significant difference in the level

of information literacy among male and female students of Al-Ain University.

Types of Research Hypothesis (Cont.)

2. Hypothesis of Difference: states that there will be a difference but

does not specify its magnitude. (degree of difference)

Example:

▫ A greater number of females than males are smokers in the study population

Types of Research Hypothesis (Cont.)

3. Hypothesis of point-prevalence: a statement that speculates almost the

exact prevalence (spread) of the situation or the outcome of a treatment program.

Example: ▫ A total of 60% of females and 30% of

males in the study populations are expatriates.

Types of Research Hypothesis (Cont.)4. Hypothesis of Association: States the extent of the relationship in terms of the effect of

different treatment groups on the dependant variable, or the prevalence of phenomenon in different populations

Example: 1. Decline of the violent behaviour rate will be three times

greater in non-violent movie group than that of the violent movie one over five years.

2. There are twice as many male smokers than female smokers in the study population

Errors in testing Hypothesis

•Faulty study design •Faulty sampling procedures •Inaccurate method of data collection •Wrong data analysis •Inappropriate statistical procedures •Incorrect conclusions

Types I & Type II errors in testing Hypothesis

•Null Hypothesis: is a statement that the thing being studied produces no effect or makes no difference.

•An example of a null hypothesis is the statement "This diet has no effect on people's weight." Usually an experimenter frames a null hypothesis with the intent of rejecting it: that is, intending to run an experiment which produces data that shows that the thing under study does make a difference.

A type I error (or error of the first kind) is the incorrect rejection of a true null hypothesis. With respect to the non-null hypothesis, it represents a false positive. Usually a type I error leads one to conclude that a supposed effect or relationship exists when in fact it doesn't. Examples of type I errors include a test that shows a patient to have a disease when in fact the patient does not have the disease, a fire alarm going off indicating a fire when in fact there is no fire or an experiment indicating that a medical treatment should cure a disease when in fact it does not.

A type II error (or error of the second kind) is the failure to reject a false null hypothesis. With respect to the non-null hypothesis, it represents a false negative. Examples of type II errors would be a blood test failing to detect the disease it was designed to detect, in a patient who really has the disease; a fire breaking out and the fire alarm does not ring or a clinical trial of a medical treatment failing to show that the treatment works when really it does.[

END Of CHAPTER 5

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