Ppdac- a scientific inquiry framework PDF

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OUTCOMES - What is statistics? o Statistics is the science of data. Methods for planning experiments, obtaining data, and then organizing, summarizing, analyzing, interpreting, presenting and drawing conclusions based on the data. - be familiar with the acronym, PPDAC; o P-roblem. Define the research question.  A clear statement of what is to be learned by defining the research questions/objectives.  What is the population of interest? The units?  What variables are under investigation?  What parameter(s) is/are of interest?  What is the goal of the research? o P-lan. Decide how to address the research problem. o D-ata. Execute your plan and examine your data. o A-nalysis. Extract meaning from your data. o C-onclusion. Interpret your results in the context of the problem - understand and identify the type of questions or processes that are relevant to the five stages of the PPDAC framework; o What is the population of interest? The units? o What variables are under investigation? o What parameter(s) is/are of interest? o What is the goal of the research? - identify or describe the target population and units of interest for a research problem; o population of interest: complete collection of all individuals/units to be studied. o Sample: subset of individuals/units from whom/which data are collected. - identify the explanatory and response variables for a research problem; o variables: a characteristic that can take on different values for different individuals/units o response variable: measures an outcome of interest in a study  aka: Dependent (attractiveness) o explanatory variable: though to explain differences or influence change in the response variable  aka: independent (heel height) - identify the nature of a research problem (i.e. causative, predictive, or descriptive); o descriptive: estimating the value of a population parameter o predictive: predicting the value of a variable for unit(s) in the population o causative: understanding how a change in the value of an explanatory variable influences the value of a response variable - define and identify parameters. o Parameter: a number that summarizes an attribute of a population  example: women walking in high-heeled shoes had a higher mean attractiveness rating then those in flat-heeled shoes (Morris et al. 2012)

o possible parameters: mean (median, mode), proportion (percentage), maximum (minimum), variance (SD, range), slope (intercept)...