Exam # 1 Study Guide Lectures: 1 - 9Lecture 1No lecture material - introductory/welcome lectureLecture 2Define the three parts of the Scientific Method1. Measurement- The act of collection of information on which a decision is based2. Evaluation- To examine and judge carefully; appraise3. Prediction- The act of predicting (by reasoning about the future)What are the three parts of Scientific Knowledge?1. Law- a concise statement of fact that has been proven time and time again, and is generally accepted as true and universal2. Theory- set of principles devised to explain a phenomena, especially one that has been repeatedly tested and can be used to make predictions about natural phenomena3. Hypothesis- an attempt to explain some basic observations before precise data has been rigorously collected and analyzedWhat are the two types of data? What are important characteristics of data?1. Quantitative- deals with numbers and can be measured2. Qualitative- deals with descriptions and can be observed3. Important characteristics: center, variability, distribution, outliersWhat is statistics and what are the two major categories?1. Definition: a collection of methods for planning experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data2. Major categories: Descriptive and Inferential KIN 4310Lecture 3Explain the main measures of Central Tendency and give the Excel function for each.1. Mean: the measure of center obtained by adding the values and dividing the total by thenumber of values - =AVERAGE(selection)2. Median: the middle value when the original data values are arranged in order of increasing (or decreasing) magnitude- =MEDIAN(selection)3. Mode: the value that occurs most frequently (data sets can be bimodal, multimodal, or have no mode)- =MODE(selection)Describe the three types of Variability and give the Excel functions for each. 1. Range- the difference between the maximum value and the minimum value- =MAX(selection) – MIN(selection)2. Standard deviation- a measure of variation of values about the mean- =STDEV(selection)3. Variance- standard deviation squared- =VAR(selection)What are three methodological approaches to Statistics?1. Descriptive- X is Y2. Correlational- X is related to Y3. Experimental- X causes YLecture 4Describe the three methodological approaches discussed in lecture 3.1. Descriptive- Observe and measure specific characteristics without attempting to modify the subjects that are being studied2. Correlational- Observations are not manipulated, merely related to one another3. Apply some treatment and then observe its effects on the subjects; Used sometimes in evaluation, but typically to explain descriptive evaluationsExplain the 5 methods of sampling.1. Random- Members of the population are selected in such a way that each individual member has an equal chance of being selected 2. Systematic- Select some starting point and then select every Nth element in the population 3. Convenience- data or results that are easy to get4. Stratified- subdivide the population into at least two different subgroups, then draw a sample from each subgroup (or stratum)5. Cluster- divide the population into sections (or clusters); randomly select some of thoseclusters; choose all members from selected clustersLecture 5Know the definitions of the following terms:1. Parameter: a numerical measurement describing some characteristic of a population2. Statistic: a numerical measurement describing some characteristic of a sample3. Sampling Error: The difference between a statistic and the associated parameter; such an error results from chance when it’s a random sample4. Non-sampling Error: Sample data that are incorrectly collected, recorded, or analyzed (such as by selecting a biased sample, using a defective instrument, or recording the data incorrectly)5. Cross-Sectional Study: Data are observed, measured, and collected at one point in time6. Retrospective Study: Data are collected from the past by going back in time7. Prospective (Longitudinal) Study: Data are collected in the future from groups (called cohorts) sharing common factors8. Confounding: Occurs in an experiment when the experimenter is not able to distinguish between the effects of different factorsWhat are the three strategies to avoid Confounding? Describe them.1. Blinding- Participant does not know whether he or she is receiving a treatment or placebo2. Matching- Select participants with similar characteristics3. Randomized controlled trial- Randomly assign participants to each experimental groupLecture 6What are Frequency Distributions and what do F.D. tables tell us?1. Definition: Lists data values (either individually or by groups of intervals), along with their corresponding frequencies or counts; Useful to summarize large sets of data2. Information from F.D. tables: tell the mode and range of the valuesKnow how to read F.D. tables and be able to recognize different types of histograms 1. Examples of histograms: Frequency polygons, dot plots, stem-and-leaf plots, pareto charts, pie charts, scatter plots, box plots, and time-series graphsLecture 7What is correlation? What is its Excel function?1. Definition: A correlation is a relationship between two variables; can be generated for predicting the value of one variable given the value of the other variable; This is appropriate for sample data that come in pairs2. =CORREL(array1,array2)What applies to correlational research?1. Definition: investigates a linear relationship between two variables2. Variables must be continuous3. Data can be presented graphically (scatter plot)4. Neither variable is truly the independent or dependent variable5. Called a bivariate relationship6. There is no causation7. Positive correlation- indicates that when X increases, so does Y8. Negative correlation- indicates that when X increases, Y decreases (and vice versa)What is the linear correlation coefficient (r) and what are the requirements?1. Definition: a numerical measure of the strength of the relationship between two variables representing quantitative data 2. Requirements:- The sample of paired (x, y) data is a random sample of independent quantitative data- Visual examination of the scatterplot must confirm that the points approximate a straight-line pattern- The outliers must be removed if they are known to be errors. The effects of any other outliers should be