HYPOTHESIS DEVELOPMENT

HYPOTHESIS DEVELOPMENT PRESENTED BY: MARTIN OTUNDO RICHARD REG NO.HDI47-C005-0151/2015 PhD( project management student)– JKUAT -2015 +254721246744

Objectives Of The Lesson. • By the the end of the lesson, the learner should be able to: • Define the term hypothesis, • Differentiate the components of hypothesis. • Differentiate between null and alternative hypothesis. • Develop null and alternative hypothesis.

Hypothesis definition • an unproved theory, proposition, supposition, etc. tentatively accepted to explain certain facts or () to provide a basis for further investigation, argument, etc. • (sciences) is a tentative inference explaining an observation, phenomenon or scientific problem that can be tested by further observation, investigation and/or experimentation.

Components of hypothesis To be complete the hypothesis must include three components: • The variables. • The population. • The relationship between the variables.

Characteristics of hypothesis • • • •

A hypothesis should be: stated clearly using appropriate terminology; testable; a statement of relationships between variables; • limited in scope (focused).

Types of hypothesis • Simple hypothesis - this predicts the relationship between a single independent variable (IV) and a single dependent variable (DV) • For example: Lower levels of exercise postpartum (IV) will be associated with greater weight retention (DV). • Where: IV = independent variable, and D V = dependent variable

Cont. of types • Complex hypothesis - this predicts the relationship between two or more independent variables and two or more dependent variables.

Example of a complex multiple independent variable hypothesis: • Low risk pregnant women (IV) who: • value health highly; • believe that engaging in health promoting behaviours will result in positive outcomes; • perceive fewer barriers to health promoting activities; • are more likely than other women to attend pregnancy-related education programmes (DV).

Cont. of types Directional hypotheses • These are usually derived from theory. • They may imply that the researcher is intellectually committed to a particular outcome. • They specify the expected direction of the relationship between variables i.e. the researcher predicts not only the existence of a relationship but also its nature.

Cont. of types Non-directional hypotheses • Used when there is little or no theory, or when findings of previous studies are contradictory. • They may imply impartiality. • Do not stipulate the direction of the relationship.

Cont. of types Associative and causal hypotheses Associative hypotheses • Propose relationships between variables - when one variable changes, the other changes. • Do not indicate cause and effect. Causal hypotheses • Propose a cause and effect interaction between two or more variables. • The independent variable is manipulated to cause effect on the • dependent variable. • The dependent variable is measured to examine the effect created by • the independent variable. •

Cont. of types Null hypotheses(H0) • These are used when the researcher believes there is no relationship between two variables or when there is inadequate theoretical or empirical information to state a research hypothesis • Null hypotheses can be: • simple or complex; • associative or causal.

Alternative hypothesis. • The alternative hypothesis, denoted by H1 or Ha, is the hypothesis that sample observations are influenced by some non-random cause.

Examples of null and alternative hypothesis • alternative hypothesis, H1 would be • “Children who eat oily fish for six months will show a higher IQ increase than children who have not.” • Therefore, your null hypothesis, H0 would be • “Children who eat oily fish for six months do not show a higher IQ increase than children who do not.”

Hypothesis development • Hypothesis is developed from research topic, problem statement, question etc. For example, in a topic :the effect of Obama's visit in tourism performance in Nairobi county , objectives could be: To examine the influence of Obama's visit in attracting foreigners to Kenya.

Null and alternative hypothesis • Null (H0) Obama's visit has no significant effect in attracting foreigners into Kenya. • Alternative hypothesis(H1) Obama's visit has a significant effect in attracting foreigners into Kenya.

Hypothesis Testing • A statistical hypothesis test is a method of statistical inference used for testing a statistical hypothesis. The Testing Process • State the relevant null and alternative hypotheses. This is important as mis-stating the hypotheses will muddy the rest of the process.

The Testing Process Cont. • Consider the statistical assumptions being made about the sample in doing the test; for example, assumptions about the statistical independence or about the form of the distributions of the observations. • Decide which test is appropriate, and state the relevant test statistic T. • Derive the distribution of the test statistic under the null hypothesis from the assumptions.

The Testing Process Cont. • Select a significance level (α), a probability threshold below which the null hypothesis will be rejected. Common values are 5% and 1%. • The distribution of the test statistic under the null hypothesis partitions the possible values of T into those for which the null hypothesis is rejected—the so-called critical region—and those for which it is not. The probability of the critical region is α.

The Testing Process Cont. • Compute from the observations the observed value tobs of the test statistic T. • Decide to either reject the null hypothesis in favor of the alternative or not reject it. The decision rule is to reject the null hypothesis H0 if the observed value tobs is in the critical region, and to accept or "fail to reject" the hypothesis otherwise.

The Testing Process Cont. N/B An alternative process is commonly used: • Compute from the observations the observed value tobs of the test statistic T. • Calculate the p-value. This is the probability, under the null hypothesis, of sampling a test statistic at least as extreme as that which was observed. • Reject the null hypothesis, in favor of the alternative hypothesis, if and only if the p-value is less than the significance level (the selected probability) threshold.

References Kothari, C.R. (2004). Research Methodology: Methods and Techniques, 2nd Revised Edition. New Age International Publishers. Mugenda, O.M. & Mugenda, A.G. (2003). Research methods: Quantitative and qualitative approaches.2nd. Rev. ed. Nairobi: Act press. Wolvesworth K. (2013). Quantitative and Qualitative Research Techniques for Humanitarian needs assessment, ACAPS

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