Research Methods- Probability And Significance

Question 1

The null (Ho) and alternative (H,) hypotheses

Answer 1

are competing statements.

The null hypothesis suggests no causal relationship exists between the independent variable (IV) and the dependent variable (DV), whereas the alternative hypothesis suggests a causal relationship.

Question 2

Deciding which hypothesis to accept and which to reject:

Answer 2

Evidence is collected by conducting controlled experiments. The researcher varies levels of the independent variable and measures the resulting change in the dependent variable. Accepting or rejecting either hypothesis depends on whether or not the results of this test match the null or alternative hypothesis.

Question 3

Variability:

Answer 3

The researcher must decide if the data collected is strong enough before rejecting the null and accepting the alternative hypothesis. Even in a well-controlled experiment, there will always be some natural variability in the data collected.
Researchers use probability to minimise the chance that they reject the null and accept an alternative hypothesis in error due to natural variability.

Question 4

0.05
AKA

Answer 4

5%
AKA
1/20

Question 5

P=<0.05:

Answer 5

Psychologists accept a 1 in 20 chance that their results are due to chance variation. As the fraction, this probability is 1/20, and 5% as a percentage. The probability is usually referred to by the decimal 0.05. P=<0.05 means there is less than a 5% probability the results gained are due to chance. (< is the symbol for less than)

Question 6

Pa<0.01:

Answer 6

Is occasionally used by psychologists, this level of significance is usually required of studies attempting to support a particularly controversial theory or if the psychologist is conducting a repication. Using the P=<0.01 level reduces the probability of accepting the alternate hypothesis in error to less than 1 in 100

Question 7

There is always a risk the results of a study are due to chance:

Answer 7

Due to the random nature of data collection, there is no level of probability we can use that completely removes the possibility of accepting the alternative hypothesis in error.

Question 8

Type I (1) error:

Answer 8

When researchers accept the alternate hypothesis (reject null) in error, the data collected has passed the level of significance, but really the findings were due to chance variation. Using P=<0.05 means this will happen in around 1 in 20 studies.

Question 9

Type II (2) error:

Answer 9

when researchers reject the alternate hypothesis (accept null) in error, the data collected has not passed the level of significance, but really the participants not acting as expected is due to chance variation hiding the causal relationship between IV & DV

Question 10

What can a researcher do to reduce the chance of a Type 1 error?

Answer 10

To reduce the chance of a Type 1 error, a researcher can decide to use a P=<0.01 level of significance, however, this then increases the likelihood of a Type 2 error.

The same is true in reverse; using P=<0.05 reduces the chance of a Type 2 error but increases the possibility of a Type 1 error compared to using P=<0.01.