Alternative Hypothesis: Females are more likely than …

CIS - On Testing More than One Hypothesis

sapir-whorf hypothesis | More Than Dragons

Consider an example with four independent groups and a continuous outcome measure. The independent groups might be defined by a particular characteristic of the participants such as BMI (e.g., underweight, normal weight, overweight, obese) or by the investigator (e.g., randomizing participants to one of four competing treatments, call them A, B, C and D). Suppose that the outcome is systolic blood pressure, and we wish to test whether there is a statistically significant difference in mean systolic blood pressures among the four groups. The sample data are organized as follows:

If four or more items are found to be defective, produc- tion is interrupted and an engineer is asked to adjust the machine.

A hypothesis leads to one or more predictions ..

So far, we have simply referred to the outcome of the teaching methods as the "performance" of the students, but what do we mean by "performance". "Performance" could mean how students score in a piece of coursework, how many times they can answer questions in class, what marks they get in their exams, and so on. There are three major reasons why we should be clear about how we operationalize (i.e., measure) what we are studying. First, we simply need to be clear so that people reading our work are in no doubt about what we are studying. This makes it easier for them to repeat the study in future to see if they also get the same (or similar) results; something called internal validity. Second, one of the criteria by which quantitative research is assessed, perhaps by an examiner if you are a student, is how you define what you are measuring (in this case, "performance") and how you choose to measure it. Third, it will determine which statistical test you need to use because the choice of statistical test is largely based on how your variables were measured (e.g., whether the variable, "performance", was measured on a "continuous" scale of 1-100 marks; an "ordinal" scale with groups of marks, such as 0-20, 21-40, 41-60, 61-80 and 81-100; or some of other scale; see the statistical guide, , for more information).

It is worth noting that these choices will sometimes be personal choices (i.e., they are subjective) and at other times they will be guided by some other/external information. For example, if you were to measure intelligence, there may be a number of characteristics that you could use, such as IQ, emotional intelligence, and so forth. What you choose here will likely be a personal choice because all these variables are proxies for intelligence; that is, they are variables used to infer an individual's intelligence, but not everyone would agree that IQ alone is an accurate measure of intelligence. In contrast, if you were measuring company performance, you would find a number of established metrics in the academic and practitioner literature that would determine what you should test, such as "Return on Assets", etc. Therefore, to know what you should measure, it is always worth looking at the literature first to see what other studies have done, whether you use the same measures or not. It is then a matter of making an educated decision whether the variables you choose to examine are accurate proxies for what you are trying to study, as well as discussing the potential limitations of these proxies.

Use of one-tailed testing is more common than we ..

Research Question: Does the data suggest that females are more likely than males to eat vegetarian meals on a regular basis?

and will also more likely be larger than one

When you conduct a piece of quantitative research, you are inevitably attempting to answer a research question or hypothesis that you have set. One method of evaluating this research question is via a process called hypothesis testing, which is sometimes also referred to as significance testing. Since there are many facets to hypothesis testing, we start with the example we refer to throughout this guide.

or hypotheses if they have more than one, will prove true.

CORRECTION: Because science classes sometimes revolve around dense textbooks, it's easy to think that's all there is to science: facts in a textbook. But that's only part of the picture. Science a body of knowledge that one can learn about in textbooks, but it is also a process. Science is an exciting and dynamic process for discovering how the world works and building that knowledge into powerful and coherent frameworks. To learn more about the process of science, visit our section on .

specified by more than one codon--usually ..

The next step is to define the variables that we are using in our study (see the statistical guide, , for more information). Since the study aims to examine the effect that two different teaching methods – providing lectures and seminar classes (Sarah) and providing lectures by themselves (Mike) – had on the performance of Sarah's 50 students and Mike's 50 students, the variables being measured are:

of binding to more than one base

By using a very straightforward example, we have only one dependent variable and one independent variable although studies can examine any number of dependent and independent variables. Now that we know what our variables are, we can look at how to set out the null and alternative hypothesis on the .