KIN 4310 Exam 1 Study Guide Lectures 1 9 Lecture 1 No lecture material introductory welcome lecture Lecture 2 Define the three parts of the Scientific Method 1 Measurement The act of collection of information on which a decision is based 2 Evaluation To examine and judge carefully appraise 3 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 universal 2 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 phenomena 3 Hypothesis an attempt to explain some basic observations before precise data has been rigorously collected and analyzed What are the two types of data What are important characteristics of data 1 Quantitative deals with numbers and can be measured 2 Qualitative deals with descriptions and can be observed 3 Important characteristics center variability distribution outliers What 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 data 2 Major categories Descriptive and Inferential Lecture 3 Explain 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 the number 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 Y 2 Correlational X is related to Y 3 Experimental X causes Y Lecture 4 Describe the three methodological approaches discussed in lecture 3 1 Descriptive Observe and measure specific characteristics without attempting to modify the subjects that are being studied 2 Correlational Observations are not manipulated merely related to one another 3 Apply some treatment and then observe its effects on the subjects Used sometimes in evaluation but typically to explain descriptive evaluations Explain 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 get 4 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 those clusters choose all members from selected clusters Lecture 5 Know the definitions of the following terms 1 Parameter a numerical measurement describing some characteristic of a population 2 Statistic a numerical measurement describing some characteristic of a sample 3 Sampling Error The difference between a statistic and the associated parameter such an error results from chance when it s a random sample 4 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 time 6 Retrospective Study Data are collected from the past by going back in time 7 Prospective Longitudinal Study Data are collected in the future from groups called cohorts sharing common factors 8 Confounding Occurs in an experiment when the experimenter is not able to distinguish between the effects of different factors What are the three strategies to avoid Confounding Describe them 1 Blinding Participant does not know whether he or she is receiving a treatment or placebo 2 Matching Select participants with similar characteristics 3 Randomized controlled trial Randomly assign participants to each experimental group Lecture 6 What 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 data 2 Information from F D tables tell the mode and range of the values Know 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 graphs Lecture 7 What 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 pairs 2 CORREL array1 array2 What applies to correlational research 1 Definition investigates a linear relationship between two variables 2 Variables must be continuous 3 Data can be presented graphically scatter plot 4 Neither variable is truly the independent or dependent variable 5 Called a bivariate relationship 6 There is no causation 7 Positive correlation indicates that when X increases so does Y 8 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 considered by calculating r with and without the outliers included 3 Know that the coefficient of determination r2 is the proportion of the variation in y that is explained by the