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Quantitative Skills for AP Biology Flashcards

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7914758980hypothesisA plausible and testable explanation for observed phenomena.0
7914758981independent variableThe experimental factor that is manipulated; the variable whose effect is being studied.1
7914758982dependent variableThe variable that responds to manipulations of the independent variable. The data.2
7914758983confounding variableAny extraneous variable that affects the variables being studied so that the results do not reflect an actual relationship between the variables under investigation.3
7914758984quantitative dataData based on quantities (numerical data).4
7914758985qualitative dataData based on qualities (non-numerical data).5
7914758986continuous dataData that can be any value on a range.6
7914758987discrete dataData that is capable of assuming only particular values. Usually the result of counting or grouping.7
7914758988control groupThe empirical group that does not receive the independent variable. Serves as a basis for comparison for evaluating the effect of the treatment.8
7914758989experimental groupThe empirical group that is exposed to the independent variable.9
7914758990correlational studyA research method that can determine the degree to which two variables are related, but cannot show which variable caused a change in the other variable.10
7914758991pseudoscienceA body of ideas clothed in the jargon and outward appearance of science but was not created with the standards required of the scientific method.11
7914758992extrapolationEstimating a value outside the range of measured data.12
7914758993statisticsThe study of the collection, organization, analysis, interpretation and presentation of data.13
7914758994population (N)A complete set of items (people, animals, etc.) that have at least one thing in common and are the subject of the statistical analysis.14
7914758995sample (n)A subset of individuals selected from the population.15
7914758996descriptive statisticsStatistics that quantitatively describe the main features of a data set, especially measures of central tendency and dispersion.16
7914758997inferential statisticsStatistics that draw conclusions from sample data. Used to test hypotheses and make estimations about the population.17
7914758998sampling biasA problem that occurs when a sample is not representative of the population from which it is drawn.18
7914758999normal distributionA unimodal, symmetrical, bell-shaped distribution of data.19
7914759000parametric dataData that show an approximate normal distribution on a histogram.20
7914759001nonparametric dataData that do not show an approximate normal distribution on a histogram. Can be qualitative data.21
7914759002frequency or count dataRecordings of discrete, or qualitative, data. Generated by counting.22
7914759003comparative statisticsStatistics that compare variables.23
7914759004association statisticsStatistics that look for correlations between variables.24
7914759005standard deviationA measurement measures the amount of variation or dispersion from the mean.25
7914759006standard errorA statistic used to make an inference about how well the sample mean matches up to the true population mean.26
7914759007linear regressionDefines a line of best fit for correlational data that can be used as a prediction of the relationship between two variables.27
7914759008histogramA graphical representation of tabulated frequencies.28
7914759009scatterplotA graph of plotted points that show the relationship between two sets of data.29
7914759010bar graphA graph drawn using rectangular bars to show how large each value is.30
7914759011box-and-whisker plotsA way of graphically depicting groups of numerical data through their quartiles.31
7914759012binsRanges of numerical values into which data are sorted in statistical analysis.32
7914759013meanA measure of central tendency determined by adding all scores together and dividing by the number of scores. Often referred to as the statistical average.33
7914759014samplingThe selection of a subset of individuals from within a statistical population to estimate characteristics of the whole population.34
791475901568-95-99.7 RuleIn a normal distribution, about 68% of values fall within 1 standard deviation of the mean, about 95% fall within 2 standard deviations of the mean, and about 99.7% fall within 3 standard deviations of the mean.35
7914759016error barsA graphical representation of the variability of data and are used on graphs to indicate the error, or uncertainty in a reported measurement.36
7914759017medianA measure of central tendency, represented by the score that separates the upper half of the scores in a distribution from the lower half.37
7914759018modeMeasure of central tendency that refers to the most frequently occurring scores.38
7914759019Chi-square testA statistical hypothesis test that measures the difference between observed frequencies and expected frequencies.39
7914759020null hypothesisHypothesis that predicts NO relationship between variables.40
7914759021alternative hypothesisHypothesis that predicts a relationship DOES EXIST between variables.41
7914759022degrees freedomThe number of ways by which a dynamic system can move without violating any constraint imposed on it. (n-1)42
7914759023critical valueA cutoff value corresponding to a given significance level.43
7914759024p-valueA predetermined choice of test certainty. The smaller the p-value, the more confidence can be claimed.44
7914759025mathematical modellingA description of a system using mathematical concepts and language.45
7914759026r-valueThe correlation coefficient that ranges from -1.0 to +1.0. The closer it is to 0, the less two variables are related.46
7914759027hypothesis testingA method of statistical inference that determines if a result is statistically significant or if it is likely to have occurred by chance alone.47
7914759028Occam's razorA principle that states that among competing hypotheses, the one with the fewest assumptions should be selected.48
7914759029type I errorFalse positive. Mistakenly reject the null hypothesis.49
7914759030type II errorFalse negative. Mistakenly reject the null hypothesis.50

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