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• ### Easy to understand

Our programs are for everyone. Lessons are simple and taught with a variety of learning styles in mind.

• ### Engaging Discussions

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• ### Real World Applications

Build confidence in your new skills with a variety of hands-on activities, quizzes, projects and real life simulations.

## Course curriculum

• 01

• Lesson x:

• 02

### Registration

• Registration Information

• Required Student Information

• 03

• 04

### Probability

• Lesson 1: How probabilities are used to represent the likelihood of a result of an experiment or a real-world event

• Quiz: Lesson 1

• Mini Challenge: Lesson 1

• Worksheet: Lesson 1

• Lesson 2: Sample space as a set that contains all possible outcomes of an experiment

• Worked Out Example: Lesson 2

• Quiz: Lesson 2

• Mini Challenge: Lesson 2

• Worksheet: Lesson 2

• Lesson 3: Distinguish between a discrete sample space and a continuous sample space

• Quiz : Lesson 3

• Mini Challenge: Lesson 3

• Worksheet : Lesson 3

• Lesson 4: Using appropriate notation and terminology pertaining to sets and set theory

• Worked Out Example: Lesson 4

• Quiz: Lesson 4

• Game Time! Find the sample space

• Game Time! Find the sample space

• Game Time! Find the discrete sample spaces

• Mini Challenge: Lesson 4

• Worksheet: Lesson 4

• Lesson 5A: Using probability formulas to complement visual problem-solving methods

• Worked Out Example: Lesson 5A

• Quiz: Lesson 5A

• Mini Challenge: Lesson 5A

• Worksheet: Lesson 5A

• Lesson 5B: Using probability formulas to complement visual problem-solving methods

• Quiz: Lesson 5B

• Mini Challenge: Lesson 5B

• Worksheet: Lesson 5B

• Lesson 6: Determining the theoretical probability, P (i.e., a value from 0 to 1), of each outcome of a discrete sample space

• Worked Out Example: Lesson 6

• Quiz: Lesson 6

• Mini Challenge: Lesson 6

• Worksheet: Lesson 6

• Lesson 7: Determining the complement of an event

• Worked Out Example: Lesson 7

• Quiz: Lesson 7

• Game Time! Fill in the blanks

• Mini Challenge: Lesson 7

• Worksheet: Lesson 7

• Lesson 8: Recognizing that the probabilities P form the probability distribution associated with the sample space

• Worked Out Example: Lesson 8

• Quiz: Lesson 8

• Game Time! Find the probability function

• Mini Challenge: Lesson 8

• Worksheet: Lesson 8

• Lesson 9: Recognizing and describing an event as a set of outcomes and as a subset of a sample space

• Worked Out Example: Lesson 9

• Quiz: lesson 9

• Mini Challenge: Lesson 9

• Worksheet: lesson 9

• Lesson 10: Solve theoretical probability problems

• Worked Out Example: Lesson 10

• Quiz: lesson 10

• Game Time! Fill in the blanks

• Mini Challenge: Lesson 10

• Worksheet: Lesson 10

• Lesson 11: The difference (and connection) between experimental and theoretical probability

• Worked Out Example: Lesson 11

• Quiz: Lesson 11

• Mini Challenge: Lesson 11

• Worksheet: Lesson 11

• Lesson 12: Determining the tendency of experimental probability to approach theoretical probability as the number of trials in an experiment increases

• Quiz: Lesson 12

• Mini Challenge: Lesson 12

• Worksheet:Lesson 12

• Lesson 13: Reflecting on the role of probability in predictions and decision making

• Quiz: Lesson 13

• Mini Challenge: Lesson 13

• Worksheet: Lesson 13

• Lesson 14: When and how to use Venn diagrams as an aid to problem solving

• Worked Out Example: Lesson 14

• Quiz: Lesson 14

• Game Time! Drag and drop

• Mini Challenge:Level 7c: Lesson 14

• Worksheet: Lesson 14

• Lesson 16: Constructing tree diagrams as a aid to problem solving

• Worked Out Example: Lesson 16

• Quiz: Lesson 16

• Mini Challenge: Lesson 16

• Worksheet: Lesson 16

• Lesson 17: Investigating connections between various ways of approaching problems (diagrams, formulas) and judging which is best

• Worked Out Example: Lesson 17

• Quiz: Lesson 17

• Game Time! Fill in the blanks

• Mini Challenge: Lesson 17

• Worksheet: lesson 17

• Lesson 18: Distinguishing between concepts of mutual exclusiveness and independence

• Worked Out Example: Lesson 18

• Quiz: Lesson 18

• Mini Challenge: Lesson 18

• Worksheet: Lesson 18

• Lesson 19: Determining whether two or more events are mutually exclusive or non-mutually exclusive

• Worked Out Example: Lesson 19

• Quiz: lesson 19

• Game Time! Find the independent events

• Game Time! Find the mutually exclusive events

• Mini Challenge: Lesson 19

• Worksheet: Lesson 19

• Lesson 20: Solving related probability problems [e.g., calculate P(~A), P(A and B), P(A or B)] using a variety of strategies (e.g., Venn diagrams, lists, formulas)

• Worked Out Example: Lesson 20

• Quiz: Lesson 20

• Mini Challenge: Lesson 20

• Worksheet: Lesson 20

• Lesson 21: Understanding and applying the symbols and criteria for independent and dependent events

• Worked Out Example: Lesson 21

• Quiz: lesson 21

• Game Time! True or false

• Mini Challenge: Lesson 21

• Worksheet: Lesson 21

• Lesson 26: Calculating and using conditional probabilities in simple cases

• Worked Out Example: Lesson 26

• Quiz: Lesson 26

• Mini Challenge: Lesson 26

• Worksheet: Lesson 26

• Lesson 27: Probability of simple combined events (including using possibility diagrams and tree diagrams, where appropriate)

• Worked Out Example: Lesson 27

• Quiz: Lesson 27

• Game Time! Fill in the blanks

• Mini Challenge: Lesson 27

• Worksheet: lesson 27

• Lesson 29: Understanding the terms permutation and combination

• Worked Out Example: Lesson 29

• Quiz: level 7c Probability: Lesson 29

• Mini Challenge: Lesson 29

• Worksheet: Lesson 29

• Lesson 30A: Recognizing the use of permutations and combinations as counting (Part 1)

• Worked Out Example: Lesson 30A

• Quiz: Lesson 30A

• Mini Challenge: Lesson 30A

• Worksheet: Lesson 30A

• Lesson 30B: Recognizing the use of permutations and combinations as counting (Part 2)

• Worked Out Example: Lesson 30B

• Quiz: Lesson 30B

• Mini Challenge: Lesson 30B

• Worksheet: Lesson 30B

• Lesson 37: Solving problems about arrangements of objects in a line, including those involving repetition and restriction

• Worked Out Example: Lesson 37

• Quiz: Lesson 37

• Game Time! Drag and drop

• Mini Challenge: Lesson 37

• Worksheet: lesson 37

• Lesson 38: Solving introductory counting problems involving the additive counting principle

• Worked Out Example: Lesson 38

• Quiz: Lesson 38

• Mini Challenge: Lesson 38

• Worksheet: Lesson 38

• Lesson 39: Solving introductory counting problems involving the multiplicative counting principle

• Worked Out Example: Lesson 39

• Quiz: level 7c Probability: Lesson 39

• Mini Challenge: Lesson 39

• Worksheet: Lesson 39

• Lesson 40: Addition and multiplication of probabilities (mutually exclusive events and independent events)

• Worked Out Example: Lesson 40

• Quiz: Lesson 40

• Mini Challenge: Lesson 40

• Worksheet: Lesson 40

• Lesson 41: Using addition and multiplication of probabilities in simple cases

• Worked Out Example: Lesson 41

• Quiz: lesson 41

• Game Time! Fill in the blanks

• Mini Challenge: Lesson 41

• Worksheet: Lesson 41

• Lesson 43: Making connections, through investigation, between combinations (i.e., n choose r) and Pascal’s triangle

• Worked Out Example: Lesson 43

• Quiz: Lesson 43

• Mini Challenge: Lesson 43

• Game Time! Memory Game

• Game Time! Drag and Drop

• Game Time! Question Set

• Worksheet: Lesson 43

• 05

### Probability Distribution

• Lesson 1: Calculating and interpreting z-scores

• Worked Out Example: Lesson 1

• Quiz: Lesson 1

• Mini Challenge: Lesson 1

• Lesson 2: Recognizing a z-score as the positive or negative number of standard deviations from the mean to a value of the continuous random variable, and solve probability problems involving normal distributions

• Worked Out Example: Lesson 2

• Quiz: Lesson 2

• Game Time! Dialog Cards

• Mini Challenge: Lesson 2

• Lesson 3: Understanding the concept of a continuous random variable versus discrete random variable

• Quiz: Lesson 3

• Mini Challenge: Lesson 3

• Lesson 4: Identifying a discrete random variable X

• Quiz: Lesson 4

• Game Time! Find the right sample spaces

• Game Time! Find the discrete random variables

• Mini Challenge: Lesson 4

• Lesson 5: Generating a probability distribution by calculating the probabilities associated with all values of a random variable

• Worked Out Example: Lesson 5

• Quiz: Lesson 5

• Mini Challenge: Lesson 5

• Lesson 6: Creating a probability distribution table and probability distribution histogram

• Worked Out Example: Lesson 6

• Quiz: Lesson 6

• Game Time! Drag and drop

• Mini Challenge: Lesson 6

• Lesson 7: Calculating weighted average

• Worked Out Example: Lesson 7

• Quiz: Lesson 7

• Mini Challenge: Lesson 7

• Lesson 8: Calculating the expected value for a given probability distribution and interpret the expected value in applications

• Worked Out Example: Lesson 8

• Quiz: Lesson 8

• Game Time! Fill in the blanks

• Mini Challenge: Lesson 8

• Lesson 11: Making connections between the frequency histogram and the probability histogram

• Quiz: Lesson 11

• Mini Challenge: Lesson 11

• Lesson 12: Recognizing conditions that give rise to a random variable that follows a binomial probability distribution

• Worked Out Example: Lesson 12

• Quiz: Lesson 12

• Mini Challenge: Lesson 12

• Lesson 13: Representing the binomial distribution numerically using a table and graphically using a probability histogram

• Worked Out Example: Lesson 13

• Quiz: Lesson 13

• Game Time! Fill in the blanks

• Mini Challenge: Lesson 13

• Worked Out Example: Lesson 14

• Quiz: Lesson 14

• Mini Challenge: Lesson 14

• Lesson 15: Representing the hypergeometric distribution numerically using a table and graphically using a probability histogram

• NO Quiz: Lesson 15

• Mini Challenge: Lesson 15

• Lesson 16: Comparing with technology and using numeric and graphical representations, the probability distributions of discrete random variables

• NO Quiz: Lesson 16

• NO Mini Challenge: Lesson 16

• Lesson 17: Solving problems involving probability distributions

• Worked Out Example: Lesson 17

• Quiz: Lesson 17

• Game Time! Fill in the blanks

• Mini Challenge: Lesson 17

• Lesson 18: Drawing up a probability distribution table relating to a given situation involving a discrete random variable X, and calculate E(X) and Var(X)

• Worked Out Example: Lesson 18

• Quiz: Lesson 18

• Game Time! Fill in the blanks

• Mini Challenge: Lesson 18

• Lesson 19&20: Binomial distribution

• Quiz: Lesson 19&20

• Mini Challenge: Lesson 19&20

• Lesson 21: Making connections between patterns in Pascal’s triangle and coefficients in binomial expansions

• Quiz: Lesson 21

• Mini Challenge: Lesson 21

• MERGED Quiz: Lesson 22

• Game Time! Dialog Cards

• MERGED Mini Challenge: Lesson 22

• Lesson 23: Using the binomial theorem to solve problems involving binomial expansions

• Worked Out Example: Lesson 23

• Quiz: Lesson 23

• Mini Challenge: Lesson 23

• Lesson 24: Using the GDC to calculate probability, expected value, standard deviation in binomial experiments

• NO Quiz: Lesson 24

• NO Mini Challenge: Lesson 24

• Lesson 36: Understanding the concept of a continuous random variable, and recall and use properties of a probability density function

• Quiz: Lesson 36

• Mini Challenge: Lesson 36

• Lesson 37: Mean, median, variance of continuous random variables and how to find percentiles

• Worked Out Example: Lesson 37

• Quiz: Lesson 37

• Game Time! Question set

• Mini Challenge: Lesson 37

• Lesson 25: Normal (Gaussian) distribution

• Quiz: Lesson 25

• Game Time! Crossword

• Mini Challenge: Lesson 25

• Lesson 26: The Poisson Distribution

• Quiz: Lesson 26

• Mini Challenge: Lesson 26

• Lesson 29: Understanding the relevance of the Poisson distribution to the distribution of random events, and use the Poisson distribution as a model

• Quiz: Lesson 29

• Mini Challenge: Lesson 29

• Lesson 27: Use formulae to calculate probabilities for the distribution Po (ƛ)

• Worked Out Example: Lesson 27

• Quiz: Lesson 27

• Game Time! Fill in the blanks

• Mini Challenge: Lesson 27

• Lesson 30: Using the Poisson distribution as an approximation to the binomial distribution where appropriate

• Quiz: Lesson 30

• Game Time! Drag and Drop

• Mini Challenge: Lesson 30

• Lesson 31: Using the normal distribution, with continuity correction, as an approximation to the Poisson distribution where appropriate

• Quiz: Lesson 31

• Game Time! Drag the Words

• Mini Challenge: Lesson 31

• Lesson 32: Central limit theorem

• Quiz: Lesson 32

• Game Time! Drag the Words

• Mini Challenge: Lesson 32

• Lesson 33: Using simulation software to explore sampling distributions

• NO Quiz: Lesson 33

• NO Mini Challenge: Lesson 33

• Lesson 35: Calculating unbiased estimates of the population mean and variance from a sample, using either raw or summarised data

• Quiz: Lesson 35

• Game Time! Dialog Cards

• NO Mini Challenge: Lesson 35

• Lesson 42A: Calculating and using the mean and standard deviation of a set of data either from the data itself or from given totals 𝛴x and 𝛴x^2, or coded totals 𝛴(x-a) and 𝛴(x-a)^2

• Quiz: Lesson 42A

• Mini Challenge: Lesson 42A

• Lesson 42B: Calculating and using the mean and standard deviation of a set of data either from the data itself or from given totals 𝛴x and 𝛴x^2, or coded totals 𝛴(x-a) and 𝛴(x-a)^2

• Quiz: Lesson 42B

• Mini Challenge: Lesson 42B

• Lesson 42C: Calculating and using the mean and standard deviation of a set of data either from the data itself or from given totals 𝛴x and 𝛴x^2, or coded totals 𝛴(x-a) and 𝛴(x-a)^2

• Quiz: Lesson 42C

• Game Time! Crossword

• Mini Challenge: Lesson 42C

• Lesson 43: Describing challenges associated with determining a continuous frequency distribution and recognize the need for mathematical models to represent continuous frequency distributions

• Quiz: Lesson 43

• NO Mini Challenge: Lesson 43

• Lesson 44: Representing, using intervals, a sample of values of a continuous random variable numerically using a frequency table

• Quiz: Lesson 44

• Game Time! Sort the Paragraphs

• Mini Challenge: Lesson 44

• Lesson 45: Interpretation of data as a boxplot

• Quiz: Lesson 45

• Game Time! Crossword

• NO Mini Challenge: Lesson 45

• Lesson 46: Recognizing that theoretical probability for a continuous random variable is determined over a range of values

• Quiz: Lesson 46

• Mini Challenge: Lesson 46

• Lesson 47: Recognizing that the probability that a continuous random variable takes any single value is zero(No video found)

• Quiz: Lesson 47

• Game Time! Drag the Words

• Mini Challenge: Lesson 47

• Lesson 48: Recognizing that the frequency polygon approximates the frequency distribution, and determine, through investigation using technology

• Quiz: Lesson 48

• Mini Challenge: Lesson 48

• Lesson 49: Comparing the effectiveness of the frequency polygon as an approximation of the frequency distribution for different sizes of the intervals(Jingda: had trouble downloading video)

• NO Quiz: Lesson 49

• Game Time! Image choice

• NO Mini Challenge: Lesson 49

• Lesson 51: Describing properties of the normal distribution, and recognize and describe situations that can be modelled using the normal distribution(No video)

• Quiz: Lesson 51

• NO Mini Challenge: Lesson 51

• Lesson 53: Recognizing that the normal distribution is commonly used to model the frequency and probability distributions of continuous random variables (CTL)

• Quiz: Lesson 53

• Game Time! Drag the Words

• NO Mini Challenge: Lesson 53

• Lesson 54: Understanding the use of a normal distribution to model a continuous random variable, and using normal distribution tables (CLT problems)

• Game Time! Find the probability

• Quiz: Lesson 54

• NO Mini Challenge: Lesson 54

• Lesson 55: Understanding the parameters of the standard normal distribution

• Quiz: Lesson 55

• NO Mini Challenge: Lesson 55

• Lesson 56: Solve problems concerning a variable X, where X~ N(𝞵,)and find the value of P(X>x1) or a related probability given the values of x1, 𝞵, σ)

• Quiz: Lesson 56

• Mini Challenge: Lesson 56

• Worksheet: Lesson 56

• Lesson 57: Calculating probabilities for normal distributions

• Quiz: Lesson 57

• Game Time! Fill in the blanks

• Mini Challenge: Lesson 57

• Worksheet: Lesson 57

• Lesson 58: Finding the value of x that corresponds with a probability for a normal distribution

• Quiz: Lesson 58

• Game Time! Drag and drop

• Mini Challenge: Lesson 58

• Worksheet: Lesson 58

• Lesson 59: Solving real world-problems involving normal distributions

• Quiz: Lesson 59

• Game Time! Drag and drop

• Mini Challenge: Lesson 59

• Worksheet: Lesson 59

• Lesson 60: Using formulas for probabilities for the binomial and geometric distributions

• Quiz: Lesson 60

• Mini Challenge: Lesson 60

• Worksheet: Lesson 60

• Lesson 61: Practical situations where binomial and geometric distributions are suitable models

• Quiz: Lesson 61

• Mini Challenge: Lesson 61

• Worksheet: Lesson 61

• Lesson 62: Using formulas for the expectation and variance of the binomial distribution and for the expectation of the geometric distribution

• Quiz: Lesson 62

• Game Time! Question set

• Mini Challenge: Lesson 62

• Worksheet: Lesson 62

• Lesson 63A: Making connections between the normal distribution and the binomial and hypergeometric distributions for increasing numbers of trials of the discrete distributions

• Quiz: Lesson 63A

• NO Mini Challenge: Lesson 63A

• Worksheet: Lesson 63A

• Lesson 63B: Making connections between the normal distribution and the binomial and hypergeometric distributions for increasing numbers of trials of the discrete distributions(No video)

• Quiz: Lesson 63B

• Mini Challenge: Lesson 63B

• Worksheet: Lesson 63B

• Lesson 64: Recalling conditions under which the normal distribution can be used as an approximation to the binomial distribution, and use this approximation, with a continuity correction, in solving problems

• Quiz: Lesson 64

• Game Time! Fill in the blanks

• Mini Challenge: Lesson 64

• Worksheet: Lesson 64

• Lesson 65: Joint Probability Distributions

• Quiz: Lesson 65

• Game Time! Drag and drop

• Mini Challenge: Lesson 65

• Game Time! Crossword

• Game Time! Flip and Learn

• Worksheet: Lesson 65

• 06

### Study Design

• Lesson 1: Reviewing Terminology

• Quiz: Lesson 1

• Game Time! Drag and Drop

• Mini Challenge: Lesson 1

• Lesson 2: Understanding the difference between types of bias: sampling and statistical

• Quiz: Lesson 2

• Game Time! Drag the Words

• Mini Challenge: Lesson 2

• Lesson 3: Explaining in simple terms why a given sampling method may be unsatisfactory

• Quiz: Lesson 3

• Game Time! Drag and Drop

• Mini Challenge: Lesson 3

• Lesson 4: Explaining the distinction between the terms population and sample

• Quiz: Lesson 4

• Mini Challenge: Lesson 4

• Lesson 5: Comparing sampling techniques

• Quiz: Lesson 5

• Mini Challenge: Lesson 5

• Lesson 6: How the use of random samples with a bias or the use of non-random samples can affect the results of a study

• Quiz: Lesson 6

• Game Time! Dialog Cards

• Mini Challenge: Lesson 6

• Lesson 7: Characteristics of an effective survey and design questionnaires or experiments for gathering data

• Quiz: Lesson 7

• Mini Challenge: Lesson 7

• Lesson 8: Collecting data from primary sources, through experimentation, or from secondary sources

• Quiz: Lesson 8

• Mini Challenge: Lesson 8

• Lesson 9: Organizing data with one or more attributes to answer a question or solve a problem

• Quiz: Lesson 9

• Game Time! Drag the Words

• Mini Challenge: Lesson 9

• Lesson 10: Reasons why variability is inherent in data

• Quiz: Lesson 10

• Game Time! Drag the Words

• Mini Challenge: Lesson 10

• Lesson 11: Distinguishing between situations that involve one variable and situations that involve more than one variable

• Quiz: Lesson 11

• Mini Challenge: Lesson 11

• Lesson 12: Recognizing types of data: qualitative vs. quantitative, continuous vs. discrete

• Quiz: Lesson 12

• Mini Challenge: Lesson 12

• Lesson 14A: Distinguishing different types of statistical data and give examples

• Quiz: Lesson 14A

• Mini Challenge: Lesson 14A

• Lesson 14B: Distinguishing different types of statistical data and give examples

• Quiz: Lesson 14B

• Game Time! Drag and Drop

• NO Mini Challenge: Lesson 14B

• Lesson 15: Observational studies

• Quiz: Lesson 15

• Mini Challenge: Lesson 15

• Lesson 16: Limitations of Observational Studies

• Quiz: Lesson 16

• Mini Challenge: Lesson 16

• Lesson 17: Designing an observational study to explore an appropriate research question

• NO Quiz: Lesson 17

• Game Time! Drag the Words

• Mini Challenge: Lesson 17

• Lesson 18: Determining and describing principles of primary data collection and criteria that should be considered in order to collect reliable primary data

• Quiz: Lesson 18

• Game Time! Image Hotspots

• Mini Challenge: Lesson 18

• Lesson 19: Experimental Studies

• Quiz: Lesson 19

• Mini Challenge: Lesson 19

• Lesson 20: Limitations of Experimental Studies

• Quiz: Lesson 20

• Game Time! Drag the Words

• Mini Challenge: Lesson 20

• Lesson 21: Purposes and uses, advantages and disadvantages of the different forms of statistical representations

• Quiz: Lesson 21

• Game Time! Image Hotspots

• Mini Challenge: Lesson 21

• 07

### Descriptive Statistics

• Lesson 1: Presenting data using a variety of methods: frequency table, relative frequency table, grouped frequency table

• Worked Out Example: Lesson 1

• Quiz: Lesson 1

• Mini Challenge: Lesson 1

• Worksheet: Lesson 1

• Lesson 2: Drawing and interpreting bar graph

• Quiz: Lesson 2

• Mini Challenge: Lesson 2

• Worksheet: Lesson 2

• Lesson 3: Drawing and interpreting stem-and-leaf diagrams

• Worked Out Example: Lesson 3

• Quiz: Lesson 3

• Mini Challenge: Lesson 3

• Worksheet: Lesson 3

• Lesson 4 : Drawing and interpreting box and-whisker plots

• Worked Out Example: Lesson 4

• Quiz: Lesson 4

• Mini Challenge: Lesson 4

• Lesson 5: Drawing and interpreting frequency histograms

• Worked Out Example: Lesson 5

• Quiz: Lesson 5

• Mini Challenge: Lesson 5

• Worksheet: Lesson 5

• Lesson 6A: Drawing and interpreting cumulative frequency graphs

• Worked Out Example: Lesson 6A

• Quiz: Lesson 6A

• Mini Challenge: Lesson 6A

• Worksheet: Lesson 6A

• Lesson 6B: Back to back stem and leaf plots

• Quiz: Lesson 6B

• NO Mini Challenge: Lesson 6B

• Game Time! Drag and Drop

• Lesson 7: Analyzing one-variable data

• Quiz: Lesson 7

• Mini Challenge: Lesson 7

• Lesson 8: Calculating mean, median, mode for data in frequency tables or grouped data

• Quiz: Lesson 8

• Mini Challenge: Lesson 8

• Worksheet: Lesson 8

• Lesson 9: Calculating range, quartile, interquartile range and standard deviation as measures of spread for a set of data

• Quiz: Lesson 9

• Mini Challenge: Lesson 9

• Worksheet: Lesson 9

• Lesson 10: Calculating the standard deviation for a set of data

• Quiz: Lesson 10

• Mini Challenge: Lesson 10

• Worksheet: Lesson 10

• Lesson 11: Using the GDC to find variance and standard deviation for grouped and ungrouped data

• Quiz: Lesson 11

• Mini Challenge: Lesson 11

• Worksheet: Lesson 11

• Lesson 13: Using the mean and standard deviation to compare two sets of data

• Quiz: Lesson 13

• Mini Challenge: Lesson 13

• Worksheet: Lesson 13

• Lesson 14: Identifying outliers and drawing modified boxplots

• Quiz: Lesson 14

• Mini Challenge: Lesson 14

• Worksheet: Lesson 14

• Game Time! Hot Spot

• Lesson 17: Solving problems involving percentiles

• Quiz: Lesson 17

• Mini Challenge: Lesson 17

• Worksheet: Lesson 17

• Lesson 18: Understanding the effects of constant changes on measures of spread

• Quiz: Lesson 18

• Mini Challenge: Lesson 18

• Worksheet: Lesson 18

• Lesson 20: Using the normal distribution to model suitable one variable data sets, and recognize these processes as strategies for one-variable data analysis

• Quiz: Lesson 20

• Mini Challenge: Lesson 20

• Lesson 21: Generating the relevant graphical summaries of one-variable data based on the type of data provided

• Quiz: Lesson 21

• Mini Challenge: Lesson 21

• Worksheet: Lesson 21

• Lesson 22: Determining which measure of central tendency should be used

• Quiz: Lesson 22

• Mini Challenge: Lesson 22

• Worksheet: Lesson 22

• Lesson 23: Interpreting, for a normally distributed population, the meaning of a statistic qualified by a statement describing the margin of error and the confidence level

• Quiz: Lesson 23

• Mini Challenge: Lesson 23

• Worksheet: Lesson 23

• Lesson 25: Role of statistical thinking in research and the scientific method

• Quiz: Lesson 25

• Mini Challenge: Lesson 25

• Game Time! Drag the Words

• Lesson 27: Understanding the nature of a hypothesis test

• Quiz: Lesson 27

• Mini Challenge: Lesson 27

• Lesson 28: Understanding the difference between one-tailed and two-tailed tests

• Quiz: Lesson 28

• Mini Challenge: Lesson 28

• Lesson 30: Formulating hypotheses and carry out a hypothesis test in the context of a single observation from a population which has a binomial or Poisson distribution

• Quiz: Lesson 30

• Mini Challenge: Lesson 30

• Lesson 32: Formulating hypotheses and carry out a hypothesis test concerning the population mean in cases where the population is normally distributed with known variance or where a large sample is used

• Quiz: Lesson 32

• Mini Challenge: Lesson 32

• Worksheet: Lesson 32

• Lesson 33: Understanding the terms Type I error and Type II error in relation to hypothesis tests

• Quiz: Lesson 33

• NO Mini Challenge: Lesson 33

• Game Time! Image Sequence

• Lesson 34: Understanding that E( x bar) = 𝞵 and that Var (x bar) = σ2/n.

• Quiz: Lesson 34

• Mini Challenge: Lesson 34

• Lesson 35: Determining and interpreting a confidence interval for a population mean in cases where the population is normally distributed with known variance or where a large sample is used

• Quiz: Lesson 35

• Mini Challenge: Lesson 35

• Worksheet: Lesson 35

• Lesson 36: Determining, from a large sample, an approximate confidence interval for a population proportion

• Quiz: Lesson 36

• NO Mini Challenge: Lesson 36

• Lesson 37: Interpreting statistical summaries to describe the characteristics of a one-variable data set and to compare two related one-variable data sets

• Quiz: Lesson 37

• Mini Challenge: Lesson 37

• Worksheet: Lesson 37

• Lesson 38: Describing how statistical summaries can be used to misrepresent one-variable data

• Quiz: Lesson 38

• Mini Challenge: Lesson 38

• Lesson 39: Making inferences, and make and justify conclusions, from statistical summaries of one-variable data orally and in writing, using convincing arguments

• Quiz: Lesson 39

• NO Mini Challenge: Lesson 39

• Game Time! Drag and Drop

• Lesson 40A: Recognizing that the analysis of two-variable data involves the relationship between two attributes

• Quiz: Lesson 40A

• NO Mini Challenge: Lesson 40A

• Worksheet: Lesson 40A

• Lesson 42: Association between two categorical variables: contingency tables — clustered, stacked bar charts

• Quiz: Lesson 42

• Mini Challenge: Lesson 42

• Lesson 43: Association between two quantitative variables: scatterplots

• Quiz: Lesson 43

• Mini Challenge: Lesson 43

• Worksheet: Lesson 43

• Lesson 44: Association between two variables: correlation and causation

• Quiz: Lesson 44

• Mini Challenge: Lesson 44

• Worksheet: Lesson 44

• Game Time! Memory Game

• Lesson 49: Using linear combinations of random variables when solving problems that result in E(aX + b) = aE(X) + b and Var(aX + b) = a^2Var(X)

• Quiz: Lesson 49

• Mini Challenge: Lesson 49

• Worksheet: Lesson 49

• Lesson 50: Using linear combinations of random variables when solving problems that result in E(aX + bY) = aE(X) + bE(Y)

• Quiz: Lesson 50

• Mini Challenge: Lesson 50

• Worksheet: Lesson 50

• Lesson 51A: Covariance of X and Y

• Quiz: Lesson 51A

• Mini Challenge: Lesson 51A

• Lesson 51B: Using linear combinations of random variables when solving problems that result in Var(aX + bY) = a²Var(X) + b²Var(Y) for independent X and Y

• Quiz: Lesson 51B

• Mini Challenge: Lesson 51B

• Worksheet: Lesson 51B

• Lesson 52: Linear combinations aX + b of a normally distributed variable

• Quiz: Lesson 52

• Mini Challenge: Lesson 52

• Lesson 53: Linear combinations aX + bY of two normally distributed variables

• Quiz: Lesson 53

• Mini Challenge: Lesson 53

• Lesson 54: Using linear combinations of random variables when solving problems if X and Y have independent Poisson distributions then X + Y has a Poisson distribution

• Quiz: Lesson 54

• NO Mini Challenge: Lesson 54

• Worksheet: Lesson 54

• Game Time! Memory Game

• Lesson 55: Strategies for two-variable data analysis

• Quiz: Lesson 55

• Mini Challenge: Lesson 55

• Lesson 56: Drawing and interpreting cumulative frequency graphs and polygons

• Quiz: Lesson 56

• Mini Challenge: Lesson 56

• Lesson 57: Using a cumulative frequency graph

• Quiz: Lesson 57

• Mini Challenge: Lesson 57

• Lesson 58: Analysis and interpretation of cumulative frequency diagrams

• Quiz: Lesson 58

• NO Mini Challenge: Lesson 58

• Lesson 59: Analysis and interpretation of cumulative frequency box-and-whisker plots

• Quiz: Lesson 59

• Mini Challenge: Lesson 59

• Lesson 60: Interpreting statistical summaries to describe the characteristics of a two variable data set and to compare two related two-variable data sets

• Quiz: Lesson 60

• Mini Challenge: Lesson 60

• Worksheet: Lesson 60

• Lesson 61: Describing how statistical summaries can be used to misrepresent two-variable data;

• Quiz: Lesson 61

• NO Mini Challenge: Lesson 61

• Worksheet lesson 61

• Lesson 62: Making inferences and justifying conclusions, from statistical summaries of two-variable data

• Quiz: Lesson 62

• NO Mini Challenge: Lesson 62

• Lesson 63: Interpreting statistics presented in the media and explain how the media, the advertising industry, and others use and misuse statistics to promote a certain point of view

• Quiz: Lesson 63

• Mini Challenge: Lesson 63

• Game Time! Image Sequencing

• 08

### Inference for categorical data: Proportions

• Lesson 1: Justifying a claim based on a confidence interval for a population proportion

• Quiz: Lesson 1

• Mini Challenge: Lesson 1

• Worksheet: Level 7c: Inference for categorical data: Proportions Lesson 1

• Lesson 2: Setting up a test for a population proportion

• Quiz: Lesson 2

• Mini Challenge: Lesson 2

• Lesson 3: Interpreting P-Values

• Quiz: Lesson 3

• Mini Challenge: Lesson 3

• Lesson 4: Concluding a test for a population proportion

• Quiz: Lesson 4

• Mini Challenge: Lesson 4

• Worksheet: Level 7c: Inference for categorical data: Proportions Lesson 4

• Lesson 5: Potential errors when performing tests

• Quiz: Lesson 5

• Mini Challenge: Lesson 5

• Worksheet: Level 7c: Inference for Categorical data: Proportions Lesson 5

• Lesson 6: Confidence intervals for the difference of two proportions

• Quiz: Lesson 6

• Mini Challenge: Lesson 6

• Worksheet: Level 7c: Inference for Categorical data: Proportions Lesson 6

• Lesson 7: Justifying a claim based on a confidence interval for a difference of population proportions

• Quiz: Lesson 7

• Mini Challenge: Lesson 7

• Lesson 8: Setting up a test for the difference of two population proportions

• Quiz: Lesson 8

• Mini Challenge: Lesson 8

• Lesson 9: Carrying out a test for the difference of two population proportions

• Quiz: Lesson 9

• Mini Challenge: Lesson 9

• Worksheet: Level 7c: Inference for Categorical data: Proportions Lesson 9

• Game Time! Memory Cards

• 09

### Inference for quantitative data: means

• Lesson 1: Setting up a test for a population mean

• Quiz: Lesson 1

• Mini Challenge: Lesson 1

• Lesson 2: Carrying out a test for a population mean

• Quiz: Lesson 2

• Mini Challenge: Lesson 2

• Worksheet: Level 7c: Inference for Quantitative data: means Lesson 2

• Lesson 3: Confidence intervals for the difference of two means

• Quiz: Lesson 3

• Mini Challenge: Lesson 3

• Lesson 4: Justifying a claim about the difference of two means based on a confidence interval

• Quiz: Lesson 4

• Mini Challenge: Lesson 4

• Worksheet: Level 7c: Inference for Quantitative data: mean Lesson 4

• Lesson 5: Setting up and carrying out a test for the difference of two population means

• Quiz: Lesson 5

• Game Time! True or False

• Mini Challenge: Lesson 5

• Worksheet: Level 7c: Inference for Quantitative data: mean Lesson 5

• 10

### Inference for categorical data: chi-square

• Lesson 1: Setting up a chi-square goodness of fit test

• Quiz: Lesson 1

• NO Mini Challenge: Lesson 1

• Lesson 2: Carrying out a chi-square test for goodness of fit test

• Quiz: Lesson 2

• Mini Challenge: Lesson 2

• Worksheet: Level 7c: Inference for categorical data Lesson 2

• Lesson 3: Expected counts in two-way tables

• Quiz: Lesson 3

• Game Time! Drag and Drop

• Mini Challenge: Lesson 3

• Worksheet: Level 7c: Inference for categorical data Lesson 3

• 11

### Inference for Quantitative data: slopes

• Lesson 1: Finding a confidence interval for the slope of a regression model

• Quiz: Lesson 1

• Mini Challenge: Lesson 1

• Worksheet: Level 7c: Inference for Quantitative data Lesson 1

• Lesson 3: Setting up a test for the slope of a regression model

• Quiz: Lesson 3

• Mini Challenge: Lesson 3

• Worksheet: Level 7c: Inference for Quantitative data Lesson 3

• Lesson 5: Skill focus: selecting an appropriate inference procedure

• Game Time! Memory Game

• No Quiz: Lesson 5

• NO Mini Challenge: Lesson 5

• 12

### Sampling Distributions

• Lesson 1: Sampling Distributions for Sample Proportions

• Quiz: Lesson 1

• NO Mini Challenge: Lesson 1

• Lesson 2: Sampling Distributions for Differences in Sample Proportions

• Quiz: Lesson 2

• NO Mini Challenge: Lesson 2

• Lesson 3: Sampling Distributions for Differences in Sample Means

• Quiz: Lesson 3

• Game Time! Flip and Learn

• NO Mini Challenge: Lesson 3

## Reviews

“Explorer Hop makes statistics enjoyable! Now I can bring my new math skills to school and show off for my teacher— she'll be so impressed.”

Student, Age 12

Ahmed

“FUN!”

Student, Age 11

Benjamin

“Statistics is pretty cool— I learned a lot in this class. I like seeing my progress as I learn all the different math subjects.”

Age, Age 11

Hana

## Pricing options

• What grade is this level for?

This level is designed for kids ages 11-12 in Grades 6 and 7.

• How is this course taught?

These (virtual) programs are designed to be completely self learnt. Students progress through the curriculum using a variety of real world applications that simulate experience, utilize creative thinking, and allow the students to test their knowledge.