STATISTICS

PART I WHAT CAN WE LEARN ABOUT STATISTICS 1.1 WHAT IS STATISTIC (A GRAMMAR OF SCIENCE) 1.2 TYPES OF STATISTICS â 1.3 A POPULATION VERSUS A SAMPLE 1.4 SOME BASIC TERMINOLOGY ABOUT STATISTICS 1.5 TYPES OF VARIABLES IN STATISTICS 1.6 CROS-SECTION VERSUS TIME-SERIES DATA WITHIN STATISTICS 1.7 SOURCES OF DATA TO DO STATISTICS 1.8 SUMMATION NOTATIONS WITH STATISTICS PART II ORGANIZING AND GRAPHING DATA WITH STATISTICS 2.1 RAW DATA 2.2 ORGANIZING AND GRAPHING QUALITATIVE DATA 2.3 ORGANIZING AND GRAPHING QUALITATIVE DATA 2.4 LEARNING SHAPES OF HISTOGRAM 2.5 LEARNING CUMULATIVE FREQUENCY DISTRIBUTION 2.6 LEARNING ABOUT STEM-AND-LEAF DISPLAYS 2.7 LEARNING ABOUT DOT PLOTS PART III DESCRIPTIVE STATISTICS WITH NUMBERS 3.1 LEARNING MEASURES OF CENTRAL TENDENCY FOR UNGROUPED DATA 3.2 LEARNING MEASURES OF DISPERSION FOR UNGROUPED DATA 3.3 LEARNING MEANS, VARIANCE, AND STANDARD DEVIATION FOR GROUPED DATA 3.4 USE OF STANDARD DEVIATION IN STATISTICS 3.5 LEARNING MEASURES OF POSITION 3.6. Learning BOX-AND-WHISKERS PLOT

PART IV PROBABILITY 4.1 EXPERIMENT OUTCOMES AND SAMPLE SPACE 4.2 CALCULATING PROBABILITY IN STATISTICS 4.3 COUNTING RULE IN STATISTICS 4.4 MARGINAL AND CONDITIONAL PROBABILITIES 4.5 MUTUALLY EXCLUSIVE EVENTS IN STATISTICS 4.6 INDEPENDENT VERSUS DEPENDENT EVENTS 4.7 COMPLEMENTARY EVENTS IN STATISTICS 4.8 INTERSECTION OF EVENTS AND MULTIPLICATION RULE 4.9 UNION OF EVENTS AND ADDITION RULE FOR STATISTICS PART V DISCRETE RANDOM VARIABLES AND THEIR PROBABILITY DISTRIBUTIONS 5.1 RANDOM VARIABLES 5.2 PROBABILITY DISTRIBUTION OF A DISCRETE RANDOM VARIABLE FOR STATISTICS 5.3 MEAN OF A DISCRET RANDOM VARIABLE 5.4 STANDARD DEVIATION OF A DISCRET RANDOM VARIABLE 5.5 FACTORIAL, COMBINATIONS, AND PERMUTATIONS 5.6 THE BINONMIAL PROBABILITY DISTRIBUTION 5.7 THE HYPERGEOMETRIC PROBABILITY DISTRIBUTION 5.8 LEARNING THE POISSON PROBABILITY DISTRIBUTION PART VI CONTINUOUS RANDOM VARIABLES AND THE NORMAL DISTRIBUTION 6.1 CONTINUOUS PROBABILITY DISTRIBUTION 6.2 THE NORMAL DISTRIBUTION 6.3 THE STANDARD NORMAL DISTRIBUTION 6.4 STANDARDIZE A NORMAL DISTRIBUTION 6.5 APPLICATIONS OF THE NORMAL DISTRIBUTION 6.6 DETERMINING THE Z AND X VALUES WHEN AN AREA UNDER THE NORMAL DISTRIBUTION CURVE IS KNOWN 6.7 THE NORMAL APPROXIMATION TO BINOMIA