Comm Health Final Flashcards
The Null Hypothesis (Ho or sometimes NH)
null hypothesis refers to a general or default position: that there is no relationship between two measured phenomena, or that a potential medical treatment has no effect.
Correlation coefficient
a measure of the linear correlation between two variables X and Y
Value of correlation coefficient
between -1 and 1; closer to -1 or 1 is a stronger; 0 is no correlation
Positive correlation
graph with positive slope; as one variable increases so does the other or as one decreases so does the other - they both go the same way
Negative correlation
graph with negative slope; as one variable increases the other decreases or as one decreases the other increases - they go opposite directions
Strength of association
Value of r, can be -r or r; 0-0.25 is little if any association; 0.26-0.49 is weak; 0.7-0.89 is high; 0.9-1 is very high
p value
usually set at 0.05; probability that findings are due to chance; this is to test the hypothesis
Hypothesis testing
a statistical decision to reject or accept the null hypothesis based on probability (p) that is at a set significance level
Statistically significant
a value of p less than or equal to the set significant level means the results are statistically significant and you reject the null hypothesis
Not statistically significant
a value of p greater than the set significant level means the results are not statistically significant and you do not reject the null hypothesis
Type 1 statistic error
researcher rejects null hypothesis and concludes that a statistically significant difference exists when in fact no true difference is present
Type 2 statistic error
researcher concludes that no statistically significant difference exists and accepts the null hypothesis when in fact a significant difference does exist
Causes: type 1 error
large sample size; p value set too high (0.05 or greater); corrected by: randomly selected sample and good study design and set p value lower than 0.05
Causes: type 2 error
too small a sample size; unrealistic measuring devices; imprecise research methods; corrected by: correction of causes
t-test used in inferential statistics
statistical measure used when comparing hypothetical difference between TWO mean scores; NH for these tests - two unrelated groups are equal; looking to see if we can show that we can reject NH and accept alternative hypothesis - two NOT equal
ANOVA test used in inferential statistics
statistical measure used when comparing hypothetical difference between THREE OR MORE mean scores
Chi-Square test used in inferential statistics
*attitudes - non-numbers; used to analyze discrete, nominally scaled data, and to test differences between frequency distributions; test independence of two categorical (descriptive) variables; helps one arrive at a p value
Standard of acceptability
p < 0.05; 1 out of 20 occurred by chance or it has nothing to do with the testing situation
Validity
degree that a study or procedure measures what it claims to be measuring; is it measuring how it claims it should?
Sensitivity
the ability of a test to correctly identify the presence of a disease
Specificity
the ability of a test to identify the absence of a disease
Reliability
the extent to which the method of measurement consistently performs
Null hypothesis
a question or statement to be answered that can be stated in a negative outcome; no benefit or significance
research question or hypothesis
a question or statement to be answered; stated negatively or positively
Positive hypothesis
Brand X significantly whitens teeth
Negative (Null) hypothesis
No statistically significant difference exists between brand X and placebo; “NO SIGNIFICANT DIFFERENCE”
Dependent variable
the outcome of interest; change in it should be observed in response to some intervention
Independent variable
the intervention; what is being manipulated to change the outcome of interest
Extraneous variables
not related to the purpose of the study BUT may influence the outcome; interfere with accurate interpretation and produce invalid research results
Placebo
should have no positive or negative effects on subjects; should seem identical in every way to the real thing