Statistics and Research Flashcards
What are the steps to implement a research study?
- identify problem
- develop research question
- develop hypothesis (null and alternative)
- methodology
- collect and analyze data
- conclusion (decisions based on data collected)
What are the steps to write a research report?
- abstract
- introduction
- literature review
- methodology
- results
- discussion
- conclusion
- implication
What is the difference between independent and dependent variables?
with independent variable, you can manipulate or control (treatment variable)
ex: how well you prepare for the exam
dependent: depends on independent (response/outcome variable)
ex: RD test score –> depends on how much you study, how well you slept, test anxiety
p value
- helps you determine the significance of your study
- p 0.05 is probability that null hypothesis is true (fail to reject the null hypothesis)
Standard deviation and the percentages away from z-score (mean)
1 SD = 68%
2 SD = 95%
3 SD = 99.7%
What is the mean?
average of all scores
(2+4+4+7+8) / 5 = 5
What is the median?
The one in the middle
(2,4,4,7,8) = 4
What is the mode?
the one featured most
(2,4,4,7,8) = 4
What are the values for the correlation coefficient (r value)?
0.0-0.4 = low (weak) correlation
0.4-0.7 = moderate correlation
0.7-1 = strong correlation
the closer r is to +1 or -1, the more closely the 2 variables are related
Quasi-experimental (observational research)
before and after, no control group
analytical/applied research
correlational studies (exploratory/ecological)
degree to which a relationship exists between 2 or more variables
uses correlation coefficient (r-value)
descriptive (basic) research
case study/case report/case series
observation of 1 or more people or events
descriptive (basic) research
qualitative studies
uses open-ended questions
interviews, observations, focus groups, surveys, questionnaires
descriptive (basic research)
cohort study (incidence)
longitudinal study
can be prospective or retrospective
analytical research
randomized clinical trial (experimental design)
assigned at random
uses experimental and control group
analytical research
cross-sectional (prevalence)
how many currently have disease
meta-analysis
quantitative
review of literature; review of numerous small studies
analytical research
cross-over design
crossed over to the other treatment
analytical research
case control
CCC = case control compares with and without disease
analytical research
What is reliability?
degree of consistency with which a test measures what it’s supposed to measure
What is validity?
truthfulness and effectiveness of a study
What is sensitivity?
true positive = sick people are sensitive = probability that a + test among a patient with disease
What is specificity?
true negative = probability of a negative test among patients without a disease = healthy people test negative
What is type I error?
false positive= you said your findings were significant (there was a difference among 2 groups) but they weren’t (there was no difference = supports null hypothesis)
ex: you reject a null hypothesis (you are saying there is a difference between groups) when in reality it’s true that there are no observed differences between groups
- a test result which incorrectly showed positive
What is type II error?
false negative = you concluded that your research was not significant when in fact it was (you said that the null hypothesis was true (no difference) but in reality the alternative hypothesis was true (there was a difference)
ex: failing to reject null hypothesis (meaning the test has not shown any difference between groups) when it’s not true (there is a difference between groups)
- result came out negative but it’s false that it’s negative
- pregnant woman was told by MD she’s not pregnant
- type II error is worse
What is Hawthorne Effect?
Placebo effect/ Elton Mayo
What is analysis of variance? (ANOVA)
a statistical test used to study group differences; tool used for validity (how accurately it measures what it’s intended to measure)
used in meta analysis
What is t-test?
a statistical test involving interval or ratio data that assesses whether the means of 2 groups are statistically different from each other
descriptive statistics
used to organize, summarize, and describe a group
inferential statistics
relationships and causalities you find in a sample and used to make generalizations (inferences) about a population
chi-test
measures the association between 2 nominal and/or ordinal variables
