Stat 201 Spring 2014 Exam 1 Study Topics Chapter 2 Type of Variables Quantitative versus categorical variable Recognizing what is not a variable at all Chapter 3 Categorical Variables Reading pie charts bar charts comparing the two Frequency table versus relative frequency table Being able to calculate a relative frequency Being able to calculate a marginal distribution Being able to calculate a conditional distribution Interpreting segmented bar charts mosaic plots Recognizing independence or dependence from mosaic plots Chapter 4 Calculating a Range and the IQR given Q1 and Q3 When to use mean and s versus median and IQR Interpreting median mean quartiles IQR range and standard deviation Interpreting shape center spread and unusual features from a histogram Comparing histograms versus stem and leaf displays Identifying symmetry skewness outliers gaps from histograms or stem and leaf Calculating a median by hand and interpreting it Know what the 5 number summary is Calculating a mean by hand and interpreting it Given the variance calculate the standard deviation Chapter 5 Interpreting side by side box plots Comparing distributions using histograms Identifying and interpreting box plot components Use of common scaling on histograms when making comparisons Recognizing a trend in a time plot Pivot Tables Pivot Charts Reading Pivot Tables in Excel Being able to recognize unusual information displayed in Pivot Tables and or Charts Being able to make recommendations to make presented information better Be familiar with data set used in class Chapter 6 Calculating Z scores comparing two values 68 95 99 7 rule Understanding Z scores s as a ruler Interpreting normal probability plots and goodness of fit tests Identifying outliers Understanding the difference between positive and negative Z scores Recognizing the normal model relationship between normal model and Z scores Nearly Normal Condition Note no use of the Z table Chapter 7 Know which type of variables we use to create a scatter plot Interpret a scatter plot Direction distinguish positive versus negative relationship Form distinguish linear versus curvy relationship Strength distinguish strong versus weak relationship Unusual Features be able to spot an outlier or groups Know the difference between explanatory and response variables Know the bounds for r Be able to match r to example scatter plots Know the 3 necessary conditions for correlation analysis Describe what it means for a correlation to be 1 0 and 1 Understand the difference between correlation and causation Have a general understanding of what lurking variables are
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