Research Methodology in CSD - Hypothesis Testing

hypothesis

Statement that describes the proposed relationship between two or more variables

Statement that describes the proposed relationship between two or more variables

Hypothesis definition

binary decision making

Testing hypotheses is a __ process

accept/reject, statistical tests

Examiner will either __/__ hypothesis based on results of __

use collected data from samples to decide whether to accept or reject the hypothesis

Goal of hypothesis testing:

risk of errors

So, minimizing __ is very important in the hypothesis testing process

1. stating the hypothesis 2. set an acceptable level of risk (alpha level) 3. choose sample size 4. determine critical value 5. compute test statistic 6. make decision about null hypothesis

What are the 6 steps of testing a hypothesis?

stating the hypothesis

Step 1 of the hypothesis testing process

descriptive statistics

organize, summarize, describe data without making inferences about the population

inferential statistics

make conclusions about populations of individuals from sample data/making an inference

inferential

hypothesis testing is an important part of __ statistics

expected

in testing a statistical hypothesis, what is __ when the hypothesis is TRUE must be known.

null

when researchers hypothesize the opposite of what they expect

null

researchers hypothesize that there is no difference between two methods or two groups, etc.

alternative hypothesis

statement of the expected result of the study

alternative hypothesis

indicates that there will be a significant difference between the groups, methods, etc. relative to the specific variable examined

set an acceptable level of risk (alpha level)

Step 2 of the hypothesis testing process

1. null is accepted when it is true 2. null hypothesis is rejected when it is false and alternative is accepted 3. null is rejected when it is true 4. null is accepted when it is false

When testing a research hypothesis, 4 possible outcomes or decisions:

type 1 error

null hypothesis is rejected when in reality it is true; should have accepted the null hypothesis

type 2 error

null hypothesis is accepted when in reality it is false; should have rejected the null and accepted alternative

alpha

The probability of a Type I error is designated by the Greek letter __

1

The probability of a Type ___ error is designated by the Greek letter alpha

alpha

[alpha/beta] is specified by researchers before data collection begins

beta

[alpha/beta] value cannot be determined prior to study unless parameters of population are known

research usually involves populations with unknown parameters

Why is beta value rarely specified in CSD?

inverse

the relationship between alpha and beta is an __ relationship

1. decrease 2. increase

an increase in alpha is accompanied by a [1] in beta, or a decrease in alpha is accompanied by an [2] in beta.

type 1

Which error is considered the more serious of the two possible errors?

1, 2

the risk of a Type __ error is more serious than the risk of a Type __ error.

.05 or less

alpha is conventionally set at a conservative level of __

p value

another name for alpha level

alpha level

another name for p value

5, 5

if your alpha level =.05 (p value), this means the researcher is willing to risk a Type I error __% of the time or __ out of 100 times

.01

when alpha =__, researcher is willing to risk a Type I error only 1% of the time or 1 out of

probability

p value stands for __ value

choosing the sample size

Step 3 of the hypothesis testing process

n

symbol for sample size

sample size

determines the probability distribution to be used and the power of the test

1. the probability distribution to be used 2. the power of the test

sample size determines 2 things:

1. standard normal 2. > 3. <

z statistic which is the [1] distribution typically requires large sample sizes (n__30) but the t statistic is appropriate for smaller samples (n__30)

power

defined as the probability of rejecting the null hypothesis when it is false or accepting the null hypothesis when it is true, which would be correct decision

powerful

a larger sample usually results in a more __ test of the null hypothesis

null, 2, low

When we draw conclusions from studies with small samples (n<10), we are at higher risk for accepting the __ hypothesis when it is false (Type __ error), meaning we are __ on POWER.

determine critical value

Step 4 of the hypothesis testing process

cut off

Statistical hypothesis testing requires a __ point that can be used to separate sample results that lead to rejecting the null hypothesis from results that lead to accepting the null hypothesis.

critical value

the cut-off point that can be used to separate sample results that lead to rejecting the null hypothesis from results that lead to accepting the null hypothesis is known as __

critical value

the value indicated on the table based on the number of participants in the study and the alpha level

1. alpha level 2. alternative hypothesis

the critical value depends on 2 things:

1. one tailed/directional 2. two tailed

what are the 2 types of alternative hypotheses?

two tailed

out of the 2 types of alternative hypotheses, which is the one most frequently used?

one tailed/directional

alternative hypothesis that predicts that one treatment or method will be better than another

two tailed

alternative hypothesis that does not predict direction; just hypothesizing that the two treatments or methods are significantly different

critical value

rejection region is dependent on the __

one tailed/directional; because rejection region is larger

Which alternative hypothesis is a more powerful analysis and why?

1. ignores possibility of unexpected difference in opposite direction 2. more vulnerable to error if distribution is not normal

two issues with one tailed/directional hypotheses:

two directional

alternative hypotheses should be __-tailed unless there is a compelling reason or evidence that result will be __.

test statistic/observed value

the finding researchers get from conducting the statistical test

accepted

When Test statistic/Observed Value ) is less than the data value for Critical value (cut-off), null hypothesis is __

rejected

When the Test Statistic/Observed Value is greater than data for Critical value, null hypothesis is __

standard score/z statistic

critical value is a __

compute the test statistic

Step 5 of the hypothesis testing process

test statistic

statistical test you will use to analyze your data

1. hypothesis 2. distribution of sample population 3. sample size 4. level of measurement

Choice of statistic depends upon 4 things:

distribution free

these tests do not depend on the population conforming to a prescribed shape, so they are __

make a decision about null

Step 6 of the hypothesis testing process

critical

After test statistic/observed value is computed, it is compared to the __ value on the table.

rejected

If test statistic (Observed Value) is greater than the Critical Value, null hypothesis is __.

accepted

If test statistic (Observed Value) is less than Critical Value, null hypothesis is __.

1. practical 2. clinically

A result may be statistically significant but may not be a [1] value - a statistically significant result may not be [2] relevant

1. effect size 2. clinical

Clinical significance is determined by several factors but the most important is [1], which helps establish evidence-based [2] practices