exam ii: ch11 Flashcards by kyle camryn

theory that is used to explain the likelihood that something will happen, no 100% guarantee

probability theory

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theory that requires absolute cut off point; assume that all of the groups in a study used to test a hypothesis are components of the same population

decision theory

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cut off point chosen before data to test hypothesis; probability level at which statistical results are judged to be significant

level of statistical significance

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null hypothesis rejected when it is true

type 1 error

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null hypothesis regarded as true when it is false

type 2 error

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conclusion/judgement based on evidence

inferences

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application of information acquired from a specific instance to a general situation

generalization

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theoretical frequency distribution of all possible values in a population; want to aim for closest to perfect bell curve

normal bell curve

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extreme score can occur in either tail of the normal curve
- extreme score = higher or lower than 95% of population

tailedness

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assumes that extreme score can occur in either tail of the normal curve
- for nondirectional hypothesis

two tailed test

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extreme values occur on a single tail of the curve
- for directional hypothesis
- more powerful than two tailed

one tailed test

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(n-1), given other score values established from the sum of these scores

degrees of freedom

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what type of statistic is used a lot in nursing studies?

descriptive (summary stats)

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type of statistics: describe/summarize
- Measures of central tendency
- Mean, median, modie
- Measures of variability
Range, standard deviation, scatter plots

descriptive statistics

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type of statistics: Predictions and generalize findings based on data
Analyze data, test hypothesis, determine causality answer research questions

inferential statistics

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freq distributions, measures of central tendency, measures of dispersion

types of descriptive statistics

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describes middle of sample, summarizes sample

measures of central tendency

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greatest freq (not always center)

mode

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sum of scores divided by number being summed (average)
- Most stable + least changed, best to summarize data

mean

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midpoint (50th percentile)

median

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range, variance, standard deviation, standardized scores

measures of dispersion

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high score minus low score, uses only two extremes, sensitive to outliers

range

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spread or dispersion of scores
- Calc ONLY at interval or ratio level of measurement

variance

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square root of variance, the average difference score

standard deviation

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raw scores thata cannot be compared + are transformed into standardized scores - Common = Z score: provides way to compare scores in similar process

standardized scores

most common standardized score; expresses deviations from the mean in terms of SD units

z-score

two scales = horizontal X axis and vertical Y axis; used to illustrate relationship

scatterplots

nonsymettrical distribution, peak of curve off center → becomes issue when data not normally distributed

skewness

known probability of including the value of the population within an interval estimate

confidence interval

compare procedures used with other stats that could have been used to greater adv

statistical suitability

based on accumulated evidence from many studies; important for verification of theoretical statements - Basis of a science - Contribute to scientific conceptualization

empirical generalizations

based on assumption that the data fall into a specific distribution, usually the normal (bell-shaped) distribution

parametric statistical tests

specific data not normally distributed

nonparametric statistical tests

t-test, ANOVA, ANCOVA, MANOVA, pearson's r

types of parametric test

chi-square, spearman's rho

types of nonparametric tesrs

type of parametric test: requires interval level of measurement, significant differences between two samples

t-test

type of parametric test: tests for differences between mean, more flexible (examine data from 2+ groups)

ANOVA

type of parametric test: examine effect of treatment apart from effect of 1+ potentially confounding variables (pretest scores, age, education, anxiety levels)

ANCOVA

type of parametric test: measure diffs in group means when 1+ dependent variable

MANOVA

type of parametric test: tests for presence of relationship between 2 variables - bivariate correlation

Pearson's r

type of non-parametric test: whether two variables are independent or related

chi-square

type of non parametric test: determine the degree of association between two sets of ranks or at the ordinal level (similar to pearson’s r)

spearman's rho

results of the study that have been translated and interpreted

findings

associated with importance to nursing body of knowledge

significance of findings

established BEFORE study begins P = 0.05 (if study done 100 times the chance of making error is 5 out of 100) P = 0.01 (if study done 100 times the chance of making error is 1 out off 100) - More difficult

level of significance

finding is UNLIKELY to have occurred by chance or fluke

statistical significance

related to practical importance of findings; value of judgement - findings can have statistical significance but not clinical P < 0.05 = null P < 0.4 = reject the null

clinical significance

Restrictions or problems in a study that may decrease the generalizability of the findings - Ex: new tool

limitations

meanings of conclusions for the body of nursing knowledge, theory, and practice (more specific than conclusion)

implications

synthesis of the findings, main points should be here

conclusions

what 2 things are studied in quantitative studies?

relationships and causality

what makes a good study

applicable to different studies

what does it mean when the mean score is an extreme value?

Population not likely to be the same as that represented by normal curve SIGNIFICANTLY DIFFERENT Means risk of making an error

which tailed test is more powerful

one tailed tests

why is analysis throughout research important

to make sure data is accurate and valid

what type of statistic is used a lot in nursing studies

descriptive statistics

where does data analysis begin

descriptive statistics

why is critically appraising results from quantitative/outcomes studies important

determine if researcher's interpretations of the results are an appropriate eval of the clinical importance of the study's findings

which measure of central tendency is the most stable and best for summarizing data

mean

what are the only 2 levels of measurement that can calculate variance

interval or ratio

what is the basis of a science?

empirical generalizations

what is bivarate correlation and what type of test is it part of?

relationship between 2 variables, part of pearson's r