Week 10 - Chapter 23 Statistical interference and statistical conclusion validity

Question 1

What is a type 1 error:

Answer 1

Mistakenly finding a difference
- rejecting the null hypothesis when the null hypothesis is true

Question 2

What is a type 2 error

Answer 2

Mistakenly not finding a difference when there is a significant difference
- do not reject null hypothesis when null hypothesis is false

Question 3

Level of significance

Answer 3

represents criterion for judging if an observed difference can be considered sampling error
- typically 5%
- at the 5% level of significance there is a 5% of rejecting the null hypothesis when it is true

Question 4

What is power

Answer 4

• can be though oof as sensitivity
• the more sensitive a test the more likely it will detect important clinical differences that truly exist
• used to avoid type 2 error

Question 5

Effect size index

Answer 5

• unites standardized value that allows for comparisons across samples and studies
• power is influenced by the size of the effect of the independent variable

Question 6

Z-ratio/Z-score

Answer 6

represents the distance between that score and the sample mean divided by the standard deviation of the distribution

Question 7

Critical region

Answer 7

• this is the region of rejection for H0
• the area above dn below a z-score

Question 8

Two-tailed test

Answer 8

• critical region is split by the noncritical region
• above and below

Question 9

critical value

Answer 9

• the value of Z that defines the critical region

Question 10

one tailed test

Answer 10

situations where a researcher has sufficient reason to porpoise an alternative hypothesis that specifics which mean will be larger a directional test can be preformed

Question 11

Statistical power

Answer 11

the power of a statistical test concerns its ability to document a real relationship between independent and dependent variables

Question 12

Violated assumptions of statistical test

Answer 12

most statistical procedures are based on a variety of assumptions about levels of measurement and variance in the data or sample from which they are collected

Question 13

Reliability and variance

Answer 13

statistical conclusions are threatened by an extraneous factors that increase variability within the data
- such as unreliable measurement, failure to standardize the protocol, environmental interferences or heterogeneity of subjects

Question 14

failure to use intention to treat analysis

Answer 14

• when data are missing or subjects do not adhere to random group assignments, analysis procedures are designed to maintain the important element of randomization

Question 15

Probability

Answer 15

• likelihood that any one event will occur (ratio and decimal)
• signified with Lowe case P

Question 16

what are the issues of probability research

Answer 16

1. implies uncertainty: predicts what should happen not what will happen
2. how well does sample estimate characteristics of population: large sample size = greater probability of sample estimating population
3. determine if observed effects likely to have occurred bye chance

Question 17

Confidence intervals

Answer 17

• use of probability to estimate population mean in 2 ways, point estimate and confidence interval

Question 18

point estimate

Answer 18

uses sample mean to estimate population mean
- can include error

Question 19

How to minimize error in confidence intervals

Answer 19

• calculate ranges of scores that should contain the population mean (confidence interval)
• boundaries of range calculated form sample mean, standard deviates and sample size
• expressed as probability percentage

Question 20

Normal sample distribution in a confidence interval

Answer 20

• Z score = +/- 2
• 95% of population within 2 standard error units of mean

Question 21

(hypothesis testing

Answer 21

• decide if observed effect is likely due to chance variation (hypothesis testing)

Question 22

Null hypothesis

Answer 22

• observed difference between groups occurred by chance

Question 23

Alternative hypothesis

Answer 23

• observed effect too large to be result of chance alone

Question 24

Non directional alternative hypothesis

Answer 24

mean change between treatment A and treatment B will be different

Question 25

Directional alternative hypothesis

Answer 25

change for treatment A will be larger than change for treatment B

Question 26

Factors affecting Power

Answer 26

• P= power: can be calculated after statistical analysis or during planning
• A = level significance: as a decreases then power decreases
• N= number of subjects; as sample size increases power increase
• E= effect size; as effect size increases power increases (how big of an affect does the intervention have)

Question 27

Z-ratio

Answer 27

• normal distribution can determine area beyond any point
• calculated Z-score for sample
• critical value: points on scale beyond which on 5% of values would be
• Z-score: for sample not in critical region there is no significant difference

Question 28

Statistical conclusions: how do we come to conclusions
1, p>alpha
2. p<alpha

Answer 28

• p-value is the probability occurred by chance
• probability (p) > a, not statistically significant and do not reject H0
• probability (p)<a there is a statistical significance difference and you accept HA

Question 29

Parametric statistics

Answer 29

• used to estimate population parameters
• validity of parametric tests depend on parametric assumptions:
  1. samples randomly drawn from population with normal distribution
  2. variances o samples being compared are roughly equal
  3. data measured on interval or ratio scales
• if parametric assumptions are unable to be met uses nonparametric