Propositions and Hypotheses

We define a proposition as a statement about observable phenomena (concepts) that may be judged as true or false. When a proposition is formulated for empirical testing, we call it a hypothesis. As a declarative statement about the relationship between two or more variables, a hypothesis is of a tentative and conjectural nature. Hypotheses have also been described as statements in which we assign variables to cases. A case is defined in this sense as the entity or thing the hypothesis talks about. The variable is the characteristic, trait, or attribute that, in the hypothesis, is imputed to the case. For example, we might create the following hypothesis:

Brand Manager Jones (case) has a higher-than-average achievement motivation (variable).

If our hypothesis was based on more than one case, it would be a generalization. For example:

Brand managers in Company Z (cases) have a higher-than-average achievement motivation (variable).

Descriptive Hypotheses

Both of the preceding hypotheses are examples of descriptive hypotheses. They state the existence, size, form, or distribution of some variable. Researchers often use a research question rather than a descriptive hypothesis. For example:

Either format is acceptable, but the descriptive hypothesis format has several advantages:

• It encourages researchers to crystallize their thinking about the likely relationships to be found.

• It encourages them to think about the implications of a supported or rejected finding.

• It is useful for testing statistical significance.

Relational Hypotheses

The research question format is less frequently used with a situation calling for relational hypotheses. These are statements that describe a relationship between two variables with respect to some case. For example, “Foreign (variable) cars are perceived by American consumers (case) to be of better quality (variable) than domestic cars.” In this instance, the nature of the relationship between the two variables (“country of origin” and “perceived quality”) is not specified. Is there only an implication that the variables occur in some predictable relationship, or is one variable somehow responsible for the other? The first interpretation (unspecified relationship) indicates a correlational relationship; the second (predictable relationship) indicates an explanatory, or causal, relationship. Correlational hypotheses state that the variables occur together in some specified manner without implying that one causes the other. Such weak claims are often made when we believe there are more basic causal forces that affect both variables or when we have not developed enough evidence to claim a stronger linkage. Here are three sample correlational hypotheses:

Young women (under 35 years of age) purchase fewer units of our product than women who are 35 years of age or older.

The number of suits sold varies directly with the level of the business cycle.

People in Atlanta give the president a more favorable rating than do people in St. Louis

By labeling these as correlational hypotheses, we make no claim that one variable causes the other to change or take on different values.

With explanatory (causal) hypotheses, there is an implication that the existence of or a change in one variable causes or leads to a change in the other variable. As we noted previously, the causal variable is typically called the independent variable (IV) and the other the dependent variable (DV). Cause means roughly to “help make happen.” So the IV need not be the sole reason for the existence of or change in the DV. Here are four examples of explanatory hypotheses:

An increase in family income (IV) leads to an increase in the percentage of income saved (DV).

Exposure to the company’s messages concerning industry problems (IV) leads to more favorable attitudes (DV) by employees toward the company.

Loyalty to a particular grocery store (IV) increases the probability of purchasing the private brands (DV) sponsored by that store.

An increase in the price of salvaged copper wire (IV) leads to an increase in scavenging (DV) on the Army firing range.

In proposing or interpreting causal hypotheses, the researcher must consider the direction of influence. In many cases, the direction is obvious from the nature of the variables. Thus, one would assume that family income influences savings rate rather than the reverse. This also holds true for the Army example. Sometimes our ability to identify the direction of influence depends on the research design. In the worker attitude hypothesis, if the exposure to the message clearly precedes the attitude measurement, then the direction of exposure to attitude seems clear. If information about both exposure and attitude was collected at the same time, the researcher might be justified in saying that different attitudes led to selective message perception or nonperception. Store loyalty and purchasing of store brands appear to be interdependent. Loyalty to a store may increase the probability of one’s buying the store’s private brands, but satisfaction with the store’s private brand may also lead to greater store loyalty.

The Role of the Hypothesis

In research, a hypothesis serves several important functions:

• It guides the direction of the study.

• It identifies facts that are relevant and those that are not.

• It suggests which form of research design is likely to be most appropriate.

• It provides a framework for organizing the conclusions that result.

Unless the researcher curbs the urge to include additional elements, a study can be diluted by trivial concerns that do not answer the basic questions posed by the management dilemma. The virtue of the hypothesis is that, if taken seriously, it limits what shall be studied and what shall not. To consider specifically the role of the hypothesis in determining the direction of the research, suppose we use this:

Husbands and wives agree in their perceptions of their respective roles in purchase decisions.

The hypothesis specifies who shall be studied (married couples), in what context they shall be studied (their consumer decision making), and what shall be studied (their individual perceptions of their roles). The nature of this hypothesis and the implications of the statement suggest that the best research design is a communication-based study, probably a survey or interview. We have at this time no other practical means to ascertain perceptions of people except to ask about them in one way or another. In addition, we are interested only in the roles that are assumed in the purchase or consumer decision-making situation. The study should not, therefore, involve itself in seeking information about other types of roles husbands and wives might play. Reflection upon this hypothesis might also reveal that husbands and wives disagree on their perceptions of roles, but the differences may be explained in terms of additional variables, such as age, social class, background, personality, and other factors not associated with their difference in gender.

What Is a Strong Hypothesis? A strong hypothesis should fulfil three conditions:

• Adequate for its purpose.

• Testable.

• Better than its rivals.

The conditions for developing a strong hypothesis are developed more fully in Exhibit 2.6

Exhibit 2.6 Checklist for Developing a Strong Hypothesis

SELF-CHECK ACTIVITY

1. What is hypothesis?
2. How do you determine the good hypothesis?
3. What is the role of hypothesis in research?