Statistics with StatCrunch by the Math Sorcerer

[SKIKDA]

Last updated 7/2019
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 9.80 GB | Duration: 15h 9m

Full College Course on Statistics with StatCrunch

What you'll learn
How to use StatCrunch for Statistics
The Difference Between Qualitative and Quantitative Data
The Difference Between Discrete and Continuous Data
Definitions of Population, Parameter, Sample, and Statistic
Levels of Measurement: Nominal, Ordinal, Interval, Ratio
Random Samples versus Simple Random Samples
Cluster Sampling, Stratified Sampling, Convenience Sampling, and Systematic Sampling
How to Construct a Frequency Table/Frequency Distribution from Scratch given the Data
How to Fill in a Frequency Table given some Information
How to Compute the Class Width from the Formula and from the Table
How to Compute the Class Limits, Frequencies, Relative Frequencies, Class Midpoints, Cumulative Frequencies, and Class Boundaries
Determine if a Frequency Table is Normal
The Definition of an Outlier
Finding the Mean and Standard Deviation from a Frequency Table
How to Read a Histogram
How to Identify the Shape of a Histogram
How to Determine if a Histogram is Normal
How to Create a Pareto Chart in StatCrunch
How to Create a Pie Chart in StatCrunch
How to Create a Stemplot(Stem and Leaf Display) in StatCrunch
How to Create a Scatter Plot in StatCrunch
How to Create a Dotplot in StatCrunch
How to Read Statistical Graphs and Recognize Bad Graphs
Understand the Notation in Statistics
Understand the Measures of Center: Mean, Median, Mode, and Midrange
Compute all the Measures of Center using StatCrunch
Understand the Measures of Variation: Range, Standard Deviation, Variance, and Coefficient of Variation
Compute all the Measures of Variation using StatCrunch
How to Compute the Coefficient of Variation by Hand
Understand Z-Scores and What they Mean Intuitively
How to Compute Z-Scores by Hand with the Formula
How to Find the Value of x Given the Z-Score
How to Compute the Maximum and Minimum Usual Values
Understand Boxplots(Box and Whisker Plots), the Five Number Summary, and the IQR(Interquartile Range)
Create a Boxplot, Find the Five Number Summary, and Find the IQR using StatCrunch
Understand How to Read Boxplots
How to Find Percentiles Given the Data with StatCrunch
Understand what a Probability Is
Understand the Various ways to Compute Probabilities
Understand The Basic Rules of Probability
Understand Complements in Probability
Understand the Addition Rule Formula for Probability and What it Means Intuitively
How to use the Addition Rule in Probability Problems
How to Compute Probabilities from a Table
Understand the Multiplication Rule for Probability
How to use the Multiplication Rule for Probability Both With and Without Replacement
Understand Conditional Probability
How to Compute Conditional Probabilities in Various Scenarios, including those which Include a Table
Understand the Multiplication Rule for Counting(AKA the Fundamental Principle of Counting) and How to Use it
Understand what a Permutation Actually Means
Understand what a Combination Actually Means
Understand the Difference between Permutations and Combinations
Compute Permutations and Combinations by Hand with the Formulas
Compute Permutations by Hand without the Formula
Compute Permutations and Combinations with StatCrunch
Compute Various Probabilities using the Theory of Counting(Multiplication Rule, Combinations, Permutations)
Understand what a Random Variable Actually Is
Determine if a Random Variable is Discrete or Continuous
Understand what a Probability Distribution Actually is
Determine if the Given Table Defines a Probability Distribution
Compute Probabilities from a Given Probability Distribution using StatCrunch and By Hand
Compute the Mean and Standard Deviation Given a Probability Distribution using StatCrunch
Understand What the Expected Value Means in the Context of the Real World(Lottery) and How to Compute it by Hand
Understand the Binomial Distribution and it's Purpose
Compute Probabilities by Hand with the Binomial Distribution
Compute Probabilities with StatCrunch and the Binomial Distribution
Compute the Mean and Standard Deviation of the Binomial Distribution by Hand
Understand the Poisson Distribution(Very Cool!)
Compute Probabilities using the Poisson Distribution by Hand
Use StatCrunch to Compute Probabilities with the Poisson Distribution
Compute the Mean and Standard Deviation of the Poisson Distribution
Construct a Probability Distribution for the Sample Means by Hand
Construct a Probability Distribution for the Sample Proportions by Hand
Understand the Normal Distribution and the Standard Normal Distribution
How to Compute Probabilities with the Normal Distribution and StatCrunch
Find the Area under the Normal Distribution with StatCrunch
Compute Z-Scores given the Area under the Normal Curve with StatCrunch
Find Percentiles with the Normal Distribution and StatCrunch
Sketch Areas under the Normal Distribution with StatCrunch
Find Cut-off Values with the Normal Distribution and StatCrunch
Find Quartiles with the Normal Distribution and StatCrunch
Understand and Use the Central Limit Theorem with StatCrunch
Construct Confidence Intervals for the Population Proportion or Population Percentage using StatCrunch
Find the Sample Size Needed to Estimate a Population Proportion or Percentage using StatCrunch
Construct Confidence Intervals for the Population Mean using Z and StatCrunch
Construct Confidence Intervals for the Population mean using T and StatCrunch
Find the Sample Size needed to Estimate a Population Mean with StatCrunch
Construct Confidence Intervals for Two Population Means using StatCrunch
Construct Confidence Intervals for Two Population Proportions using StatCrunch
Perform a Full Hypothesis Test for a Population Proportion or Percentage with StatCrunch
Perform a Full Hypothesis Test for a Population Mean with StatCrunch
Perform a Full Hypothesis Test for Two Population Means with StatCrunch
Perform a Full Hypothesis Test for Two Population Proportions with StatCrunch
Perform a Full Hypothesis Test for Dependent Data with StatCrunch
How to Compute P-Values, Test Statistics, and Critical Values for Various Hypothesis Tests with StatCrunch
Understand the Basics of Linear Correlation and What it Means Intuitively
Understand what the Linear Correlation Coefficient Actually Means and Represents
How to Determine if there is a Linear Correlation Both Mathematically and Graphically
How to Compute the Linear Correlation Coefficient and Coefficient of Determination using StatCrunch
How to Compute the Least Squares Line(Regression Line) using StatCrunch
How to Make Predictions when there is a Linear Correlation using StatCrunch
How to Make Predictions when there is not a Linear Correlation using StatCrunch

Requirements
Must have StatCrunch or Purchase Access to StatCrunch

Description
This is a complete college level course in Statistics which uses StatCrunch.****In order to fully benefit from this course, you must have access to StatCrunch.***If you are currently taking Statistics using StatCrunch or plan to take Statistics in College using StatCrunch, then this is the PERFECT COURSE!!!Basically just,1) Watch the videos, and try to follow along with a pencil and paper, take notes! 2) Eventually you should be able to do the problems before I do them. Try! Keep watching until you can do the problems on your own3) Repeat!If you finish even 50% of this course you will know A LOT of Statistics and more importantly your Statistics skills will improve a ton!Statistics is an awesome class because it gives you real life examples of how mathematics is used. This is really the ideal course for anyone who wants to learn Statistics and already has StatCrunch or is willing to get it. This course is especially useful for those who are taking a course in college and using StatCrunch. If you are, then good chance this will help you quite a bitI hope you enjoy watching these videos and working through these problems as much as I have

Overview
Section 1: Introduction to Statistics

Lecture 1 Introduction to Statistics

Lecture 2 Discrete and Continuous Data

Lecture 3 Populations, Samples, Parameters, and Statistics

Lecture 4 Levels of Measurement: Nominal, Ordinal, Interval, Ratio

Lecture 5 Random Samples and Simple Random Samples

Lecture 6 Stratified, Cluster, Systematic, and Convenience Sampling

Lecture 7 Qualitative versus Quantitative Data Example

Lecture 8 Discrete or Continuous Example 1

Lecture 9 Discrete or Continuous Example 2

Lecture 10 Statistic or Parameter Example 1

Lecture 11 Statistic or Parameter Example 2

Lecture 12 Level of Measurement Example 1

Lecture 13 Level of Measurement Example 2

Lecture 14 Level of Measurement Example 3

Lecture 15 Level of Measurement Example 4

Lecture 16 Sampling Technique Example 1

Lecture 17 Sampling Technique Example 2

Lecture 18 Sampling Technique Example 3

Lecture 19 Sampling Technique Example 4

Section 2: Frequency Tables

Lecture 20 Frequency Table and Class Width Example 1

Lecture 21 Frequency Table and Class Width Example 2

Lecture 22 Find the Total Number given the Frequency Table

Lecture 23 How to Compute Relative Frequencies

Lecture 24 Class Limits, Class Width, Class Midpoints, and Class Boundaries Example 1

Lecture 25 Class Limits, Class Width, Class Midpoints, and Class Boundaries Example 2

Lecture 26 Determine if the Frequency Table is Normal Example 1

Lecture 27 Determine if the Frequency Table is Normal Example 2

Lecture 28 How to Find the Frequencies in a Frequency Table

Lecture 29 How to Find Cumulative Frequencies Example 1

Lecture 30 How to Find Cumulative Frequencies Example 2

Lecture 31 Definition of an Outlier

Lecture 32 Constructing a Relative Frequency Distribution

Lecture 33 Frequency Table with Relative Frequencies, Cumulative Frequencies, and Midpoints

Lecture 34 Class Boundaries in a Frequency Table with Decimals

Lecture 35 Mean and Standard Deviation from a Frequency Table Example 1

Lecture 36 Mean and Standard Deviation from a Frequency Table Example 2

Section 3: Histograms

Lecture 37 Reading a Histogram Example 1

Lecture 38 Reading a Histogram Example 2

Lecture 39 Reading a Histogram Example 3

Lecture 40 Identify the Shape of the Histogram

Lecture 41 Determine if the Histogram is Normal Example 1

Lecture 42 Determine if the Histogram is Normal Example 2

Lecture 43 Determine if the Histogram is Normal Example 3

Lecture 44 Conceptual Examples with Histograms

Section 4: Statistical Graphs in StatCrunch

Lecture 45 Pie Chart in StatCrunch

Lecture 46 Stemplot in StatCrunch

Lecture 47 Dotplot in StatCrunch

Lecture 48 Pareto Chart in StatCrunch

Lecture 49 Scatterplot in StatCrunch

Section 5: Dotplots, Stemplots, Pareto Charts, Pie Charts, and Scatter Plots

Lecture 50 Dotplot Example

Lecture 51 Stemplot Example

Lecture 52 Pareto Chart Example 1

Lecture 53 Pareto Chart Example 2

Lecture 54 Misleading Graph Example

Lecture 55 Some Conceptual Examples

Section 6: Measures of Center and Variation

Lecture 56 Measures of Center: Mean, Median, Mode, and Midrange

Lecture 57 Measures of Center Example 1

Lecture 58 Measures of Center Example 2

Lecture 59 Measures of Center Example 3

Lecture 60 Mode in StatCrunch

Lecture 61 Measures of Center Example 4

Section 7: Measures of Variation

Lecture 62 Introduction to Measures of Variation

Lecture 63 Notation in Statistics

Lecture 64 Notation Example Problem

Lecture 65 Measures of Variation Example 1

Lecture 66 Measures of Variation Example 2

Lecture 67 Mean, Standard Deviation, and Variance in StatCrunch

Lecture 68 Mean, Range, and Standard Deviation from a Stemplot Example

Lecture 69 Coefficient of Variation Example 1

Lecture 70 Coefficient of Variation Example 2

Lecture 71 Coefficient of Variation Example 3

Lecture 72 Coefficient of Variation Example 4

Section 8: Measures of Relative Standing

Lecture 73 Introduction to Z-Scores

Lecture 74 Z-Score Example 1

Lecture 75 Z-Score Example 2

Lecture 76 Z-Score Example 3

Lecture 77 Z-Score Example 4

Lecture 78 Z-Score Example 5

Lecture 79 Z-Score Example 6

Lecture 80 Z-Score Example 7

Lecture 81 Maximum and Minimum Usual Values

Section 9: Box and Whisker Plots

Lecture 82 Introduction to Boxplots with StatCrunch

Lecture 83 Boxplot and Five Number Summary Example 1

Lecture 84 Boxplot and Five Number Summary Example 2

Lecture 85 Boxplot and Five Number Summary Example 3

Lecture 86 Percentiles with StatCrunch

Lecture 87 Percentile Example 1

Lecture 88 Percentile Example 2

Lecture 89 Some Conceptual Questions

Section 10: Probability

Lecture 90 Introduction to Probability

Lecture 91 Three Ways to Generate Probabilities

Lecture 92 Complements in Probability

Lecture 93 Basic Probability Example 1

Lecture 94 Basic Probability Example 2

Lecture 95 Basic Probability Example 3

Lecture 96 Basic Probability Example 4

Lecture 97 Basic Probability Example 5

Lecture 98 Basic Probability Example 6

Lecture 99 Basic Probability Example 7

Lecture 100 Basic Probability Example 8

Lecture 101 Basic Probability Example 9

Lecture 102 Basic Probability Example 10

Lecture 103 Basic Probability Example 11

Lecture 104 Basic Probability Example 12

Lecture 105 Basic Probability Example 13

Lecture 106 Basic Probability Example 14

Lecture 107 Basic Probability Example 15

Lecture 108 Basic Probability Example 16

Section 11: Addition Rule for Probability

Lecture 109 The Addition Rule for Probability

Lecture 110 Addition Rule with Table Example 1

Lecture 111 Addition Rule With Table Example 2

Lecture 112 Addition Rule with Table Example 3

Lecture 113 Addition Rule with Table Example 4

Lecture 114 Addition Rule with Table Example 5

Lecture 115 Addition Rule with Table Example 6

Section 12: Multiplication Rule for Probability

Lecture 116 The Multiplication Rule for Probability

Lecture 117 Multiplication Rule for Probability Example 1

Lecture 118 Multiplication Rule for Probability Example 2

Lecture 119 Multiplication Rule for Probability Example 3

Lecture 120 Multiplication Rule for Probability Example 4

Lecture 121 Multiplication Rule for Probability Example 5

Lecture 122 Multiplication Rule for Probability Example 6

Lecture 123 Multiplication Rule for Probability Example 7

Lecture 124 Multiplication Rule for Probability Example 8

Section 13: Conditional Probability

Lecture 125 Conditional Probability Example 1

Lecture 126 Conditional Probability Example 2

Lecture 127 Conditional Probability Example 3

Lecture 128 Conditional Probability Example 4

Lecture 129 Conditional Probability Example 5

Lecture 130 Conditional Probability Example 6

Lecture 131 Conditional Probability Example 7

Section 14: Counting Theory

Lecture 132 Multiplication Rule Example 1

Lecture 133 Multiplication Rule Example 2

Lecture 134 Multiplication Rule Example 3

Lecture 135 Multiplication Rule Example 4

Lecture 136 Multiplication Rule Example 5

Lecture 137 Multiplication Rule Example 6

Lecture 138 Introduction to Combinations and Permutations

Lecture 139 Combinations Example 1

Lecture 140 Combinations Example 2

Lecture 141 Combinations by Hand with the Formula Example

Lecture 142 StatCrunch and Permutations Example 1

Lecture 143 StatCrunch and Permutations Example 2

Lecture 144 StatCrunch and Combinations Example 1

Section 15: More Counting Theory with Probability

Lecture 145 Example 1

Lecture 146 Example 2

Lecture 147 Example 3

Lecture 148 Example 4

Lecture 149 Example 5

Lecture 150 Example 6

Lecture 151 Example 7

Lecture 152 Example 8

Section 16: Probability Distributions

Lecture 153 Introduction to Random Variables

Lecture 154 Discrete Probability Distributions

Lecture 155 Mean and Standard Deviation for Random Variables

Lecture 156 The Expected Value Intuitive Explanation

Section 17: Probability Distributions Examples

Lecture 157 Example 1

Lecture 158 Example 2

Lecture 159 Example 3

Lecture 160 Example 4

Lecture 161 Example 5

Lecture 162 Example 6

Section 18: The Binomial Distribution

Lecture 163 The Binomial Distribution

Lecture 164 Choosing Inequality Symbols

Lecture 165 Binomial Distribution Example by Hand

Lecture 166 Mean and Standard Deviation of the Binomial Distribution

Lecture 167 Example 1

Lecture 168 Example 2

Lecture 169 Example 3

Lecture 170 Example 4

Lecture 171 Example 5

Lecture 172 Example 6

Lecture 173 Example 7

Section 19: The Poisson Distribution

Lecture 174 Introduction to the Poisson Distribution

Lecture 175 Poisson Distribution Example by Hand

Lecture 176 Poisson Distribution StatCrunch Example

Lecture 177 Example 1

Lecture 178 Example 2

Lecture 179 Example 3

Section 20: Sampling Distributions

Lecture 180 Probability Distribution for the Sample Means

Lecture 181 Probability Distribution for the Sample Proportions

Section 21: The Normal Distribution

Lecture 182 Full Introduction to the Normal Distribution

Lecture 183 Normal Distribution with StatCrunch Example 1

Lecture 184 Normal Distribution with StatCrunch Example 2

Lecture 185 Normal Distribution with StatCrunch Example 3

Lecture 186 Normal Distribution with StatCrunch Example 4

Lecture 187 Normal Distribution with StatCrunch Example 5

Lecture 188 Normal Distribution with StatCrunch Example 6

Lecture 189 Normal Distribution with StatCrunch Example 7

Lecture 190 How to Compute Percentiles with the Normal Distribution

Lecture 191 Cut-off Value with the Normal Distribution Example 1

Lecture 192 Cut-off Value with the Normal Distribution Example 2

Section 22: The Normal Distribution: More Practice Problems

Lecture 193 Example 1: Probability Question

Lecture 194 Example 2: Probability Question

Lecture 195 Example 3: Finding the Z-Score

Lecture 196 Example 4: Finding the Z-Score

Lecture 197 Example 5: Sketching the Area

Lecture 198 Example 6: Sketching the Area

Lecture 199 Example 7: Sketching the Area

Lecture 200 Example 8: Finding a Percentile

Lecture 201 Example 9: Finding the Area

Lecture 202 Example 10: Finding the Area

Lecture 203 Example 11: Finding x Given the Area

Lecture 204 Example 12: Probability Question

Lecture 205 Example 13: Finding a Percentile

Lecture 206 Example 14: Finding the First Quartile

Lecture 207 Example 15: Finding a Percentage

Lecture 208 Example 16: Finding a Cut-off Value

Section 23: The Central Limit Theorem

Lecture 209 Introduction to the Central Limit Theorem

Lecture 210 Central Limit Theorem Example 1

Lecture 211 Central Limit Theorem Example 2

Lecture 212 Central Limit Theorem Example 3

Lecture 213 Central Limit Theorem Example 4

Section 24: Estimating Population Proportions

Lecture 214 Confidence Interval for a Population Proportion Example 1

Lecture 215 Confidence Interval for a Population Proportion Example 2

Lecture 216 Confidence Interval for a Population Proportion Example 3

Lecture 217 Confidence Interval for a Population Proportion Example 4

Lecture 218 Confidence Interval for a Population Proportion Example 5

Lecture 219 Confidence Interval for a Population Proportion Example 6

Lecture 220 Sample Size needed to Estimate a Population Proportion Example 1

Lecture 221 Sample Size needed to Estimate a Population Proportion Example 2

Lecture 222 Sample Size needed to Estimate a Population Proportion Example 3

Section 25: Estimating Population Means

Lecture 223 Introduction to Confidence Intervals for the Mean: Z versus T

Lecture 224 Confidence Interval and Intepretation for a Population Mean by Hand

Lecture 225 Confidence Interval for a Mean using StatCrunch Example 1

Lecture 226 Confidence Interval for a Mean using StatCrunch Example 2

Lecture 227 Confidence Interval for a Mean using StatCrunch Example 3

Lecture 228 Confidence Interval for a Mean using StatCrunch Example 4

Lecture 229 Confidence Interval for a Mean using StatCrunch Example 5

Lecture 230 Confidence Interval for a Mean using StatCrunch Example 6

Lecture 231 Confidence Interval for a Mean using StatCrunch Example 7

Lecture 232 Confidence Interval for a Mean using StatCrunch Example 8

Lecture 233 Confidence Interval for a Mean using StatCrunch Example 9

Lecture 234 Sample Size needed to Estimate a Population Mean with StatCrunch

Section 26: Hypothesis Testing

Lecture 235 Introduction to Hypothesis Testing

Lecture 236 How to Set up the Null and Alternative Hypothesis

Lecture 237 How to Determine the Conclusion of a Hypothesis Test

Lecture 238 Determining the Conclusion of a Hypothesis Test

Section 27: Hypothesis Testing for a Population Proportion

Lecture 239 Example 1

Lecture 240 Example 2

Lecture 241 Example 3

Lecture 242 Example 4

Lecture 243 Example 5

Section 28: Hypothesis Testing for a Population Mean

Lecture 244 Example 1

Lecture 245 Example 2

Lecture 246 Example 3

Lecture 247 Example 4

Section 29: Hypothesis Testing for Two Population Proportions

Lecture 248 Example 1

Lecture 249 Example 2

Section 30: Confidence Intervals for Two Proportions

Lecture 250 How to Interpret Confidence Intervals for Two Proportions

Lecture 251 Confidence Level for a Confidence Interval in relation to a Hypothesis Test

Lecture 252 Confidence Interval for Two Proportions Example in StatCrunch

Section 31: Hypothesis Tests and Confidence Intervals for Two Population Means

Lecture 253 Example 1

Lecture 254 Example 2

Lecture 255 Example 3

Section 32: Hypothesis Tests for Paired Data: Dependent Samples

Lecture 256 Example 1

Lecture 257 Example 2

Lecture 258 Example 3

Lecture 259 Example 4

Lecture 260 Example 5

Section 33: Computing P-Values with StatCrunch for One Tailed Tests

Lecture 261 P-Value Example 1

Lecture 262 P-Value Example 2

Lecture 263 P-Value Example 3

Lecture 264 P-Value Example 4

Section 34: Computing Critical Values in StatCrunch for One Tailed Tests

Lecture 265 Critical Value Example 1

Lecture 266 Critical Value Example 2

Lecture 267 Critical Value Example 3

Section 35: Computing P-Values, Test Statistics, and Critical Values for Two-Tailed Tests

Lecture 268 P-Value and Test Statistic for Hypothesis Test for Two Proportions in StatCrunch

Lecture 269 P-Value and Test Statistic for a Hypothesis Test for Two Means with StatCrunch:1

Lecture 270 P-Value and Test Statistic for a Hypothesis Test for Two Means with StatCrunch:2

Lecture 271 Critical Value for a Two Tailed Test Example 1

Lecture 272 Critical Value for a Two Tailed Test Example 2

Section 36: Correlation and Regression

Lecture 273 Introduction to Correlation

Lecture 274 How to Make Predictions in Regression Analysis

Lecture 275 Least Squares Line, Correlation Coefficient, and Coefficient of Determination

Section 37: Correlation and Regression: More Examples

Lecture 276 Example 1

Lecture 277 Example 2

Lecture 278 Example 3

Lecture 279 Example 4

Lecture 280 Example 5

Lecture 281 Example 6

Lecture 282 Example 7

Lecture 283 Example 8

Anyone Currently Taking a Course using StatCrunch,Anyone who wants to Learn Statistics using StatCrunch(must have StatCrunch)

Buy Premium Account From My Download Links & Get Fastest Speed.

[To see links please register or login]

[To see links please register or login]

[To see links please register or login]