PSYC295 - Test 2

Type I Error

An error that occurs when a researcher concludes that the independent variable had an effect on the dependent variable, when no such relation exists; a "false positive" REJECTING THE NULL WHEN THEY SHOULD FAIL TO REJECT THE NULL (NO SIGNIFICANT CHANGE) La

Type II Error

An error that occurs when a researcher concludes that the independent variable had no effect on the dependent variable, when in truth it did; a "false negative" FAILING TO REJECT THE NULL WHEN THEY SHOULD REJECT THE NULL (SIGNIFICANT CHANGE)

50.00+33.49=0.8849

A vertical line is drawn through a normal distribution at z = 1.20. What proportion of the distribution is on the left-hand side of the line?

A normal distribution has ? = 80 and ? = 10. What is the probability of randomly selecting a score greater than 75 from this distribution?

50.00+19.15=69.15

What z-score values form the boundaries for the middle 60% of a normal distribution?

+0.84 & -0.84 because 30% mean to z value

What z-score value separates the top 10% of a normal distribution from the bottom 90%

1.28 because 10% in tail

For a normal distribution, what is the proportion in the tail beyond z = -2.00?

0.0228

? = 12. SE of 3, then the sample size is n = 4?

No because ?M = ?/Sq of n so 12/2=6.

? =

expected value for the distribution of sample means

How big should a sample be for normal distribution?

30+

Increasing sample size

decreases the standard error and has no effect on the risk of a Type I error.

Describe the relationship: the a-level, the size of the critical region, and the risk of a Type I error.

a-level ^, critical region ^, Type I error risk ^

Whenever you reject the null, you risk a Type II error.

No.

n = 9 M = 66 ? = 75 ? = 12 two-tailed test with an alpha of .05

SE = 4.00 and z=-2.25. Reject the null (significant difference)

n = 36 M = 4.9 ? = 4.1 ? = 1.8 two-tailed test with alpha = .05

pos/neg 1.96 SE = .30 and z = 2.67. Reject the null (significant difference)

Random sample

a sample in which every element in the population has an equal chance of being selected

convenience sample

only members of the population who are easily accessible are selected

generalizability

the extent to which findings can be applied to the larger population from which the sample is drawn

replication

Repeating the essence of a research study, usually with different participants in different situations, to see whether the basic finding extends to other participants and circumstances

volunteer sample

This exists when people volunteer to be part of a study. The problem with this is that it tends to overrepresent people with strong opinions.

personal probability

when the probability is subjective and represents your personal degree of belief

probability

the likelihood that a particular event will occur
=Successes/trials

expected relative-frequency probability

The likelihood of an event occurring based on the actual outcome of many, many trials

trial

Refers to the occasion that a given procedure is carried out.

outcome

a possible result of an experiment.

success

In reference to probability, refers to the outcome for which we're trying to determine probability

control group

the group that does not receive the experimental treatment.

experimental group

subjects in an experiment to whom the independent variable is administered

null hypothesis

A statement , The hypothesis that states there is no difference between two or more sets of data.

research hypothesis

States that a relationship or direction exists between variables. Is scientific, substantive, theoretical, & declarative.

normal curve

a symmetrical curve representing the normal distribution

standardization

defining meaningful scores by comparison with the performance of a pretested group

z score

a measure of how many standard deviations you are away from the norm (average or mean)

z distribution

The number of standard deviations away a random variable is from the population mean ;
z = (variable - population mean)\(standard deviation)

standard normal distribution

The normal distribution with mean � = 0 and standard deviation ? = 1. Its ordinary scores are the same as its z-scores.

central limit theorem

The theory that, as sample size increases, the distribution of sample means of size n, randomly selected, approaches a normal distribution.

distribution of means

The distribution of all possible sample means for all possible samples from a population

standard error

the standard deviation of a sampling distribution

z test

The statistical formula to determine the z-score of a particular raw score.

assumption

a characteristic that we ideally require the population from which we are sampling to have so that we can make accurate inferences.

parametric test

is an inferential statistical analysis based on a set of assumptions about the population

nonparametric test

an inferential statistical analysis that is not based on a set of assumptions about the population

robust hypothesis

one that produces fairly accurate results even when the data suggest that the population might not meet some of the assumptions.

critical values

The values that lie exactly on the boundary of the region of rejection.

critical region

the most extreme portion of a distribution of statistical values for the null hypothesis determined by the alpha level (typically 5%)

p level

the probability that the obtained correlation or difference between experimental conditions would be expected by chance.

statistically significant

an observed effect so large that it would rarely occur by chance, an observed effect so large that it would rarely occur by chance

one-tailed test

when region of rejection is entirely under one tail of the distribution

two-tailed test

extreme test statistic is in either tail of distribution +/-

Risks of sampling & probability

sample might not represent larger pop
we might not know it's misleading
we might reach inaccurate conclusions
we might make decisions based on bad info

rewards of sampling & probability

sample represents a larger pop
increase our level of confidence in results
accurate conclusions/low cost
remain open minded - know samples can mislead
make wiser decisions based on evidence

Calculating probability

1. determine total # of trials
2. Determine # of successful out comes
3. Divide: # of successes/total # of trials

Gamblers fallacy

mistaken notion that the probability of a particular event changes with a long stream of the same event.
probability is not certainty unless it's 1 or 0
long run patterns, not guarantees.

reject the null/null hypothesis

you found a difference. no mean change or difference. fail to reject the null hypothesis. non directional = two tailed

fail to reject/research hypothesis

you did not find a difference. mean change or difference, reject the null hypothesis. directional = one tailed

Central limit theorem

The theory that, as sample size increases, the distribution of sample means of size n, randomly selected, approaches a normal distribution.