AIM: How can we assess our understanding of probability and statistics?
HW: Prepare for tomorrow Announcement: Probability & Statistics Exam Thursday  3/29/18 Simple/Compound Probability Probability Simulations Measures of Central Tendency Variability (M.A.D., IQR) Samples and Populations Comparing Samples Do Now: Please clear your desk except for a pencil, calculator, and index card cheat sheet. Classwork: Probability and Statistics exam Resources: AIM: How can we prepare for our unit exam?
HW: Prepare for tomorrow Announcement: Probability & Statistics Exam Thursday  3/29/18 Simple/Compound Probability Probability Simulations Measures of Central Tendency Variability (M.A.D., IQR) Samples and Populations Comparing Samples Do Now: Create a list of all the topics you will be responsible for tomorrow's exam. Rank them in order for what you know best to least (1 being the best) Classwork: Students worked to create a cheat sheet for probability and statistics concepts and topics. This reinforced study strategies and engaged student in important metacognitive selfassessment. Resources: AIM: How can we use data to draw inferences about a population?
HW: Exam Reflection Sheet / Create an exam study guide Announcement: Probability & Statistics Exam Thursday  3/29/18 Simple/Compound Probability Probability Simulations Measures of Central Tendency Variability (M.A.D., IQR) Samples and Populations Comparing Samples Do Now: You want to know how many red M&Ms are in a 3 pound package. To save time, you randomly take out a sample of 20 M&Ms and count 6 red. If the package says there are a total of 481 M&Ms in the entire thing, predict how many will be red. Explain your reasoning. Classwork: Students watch Yellow Starbursts video from Dan Meyer. Using our knowledge of statistics and probability, students predicted how many double packs of Starbursts contain exactly 1 yellow starburst, and how many packs contained exactly two yellow starbursts. Resources: AIM: How can we use samples to make predictions about populations?
HW: Create an exam study guide Announcement: Probability & Statistics Exam Thursday  3/29/18 Simple/Compound Probability Probability Simulations Measures of Central Tendency Variability (M.A.D., IQR) Samples and Populations Comparing Samples Do Now: Is each equation true or false? Explain your reasoning. 1) 8=(8+8+8+8)÷3 2) (10+10+10+10+10)÷5=10 3) (6+4+6+4+6+4)÷6=5 Classwork: A population is a set of people or things that we want to study. Here are some examples of populations: •All people in the world •All seventh graders at a school •All apples grown in the U.S. A sample is a subset of a population. Here are some examples of samples from the listed populations: •The leaders of each country •The seventh graders who are in band •The apples in the school cafeteria When we want to know more about a population but it is not feasible to collect data from everyone in the population, we often collect data from a sample. In the lessons that follow, we will learn more about how to pick a sample that can help answer questions about the entire population. Resources: AIM: How can we compare two groups using measures of center and variability? HW: 811 Practice (below) / Schoology Ratios and Proportions Quiz 1 Due Monday 3/19/18 Announcement: HAPPY PI DAY Do Now: What do you notice? What do you wonder? Classwork: In 6th grade, students learned how to calculate the measures of central tendency (mean, median, mode) to describe a data set. As a review, here's how to calculate each: Mean (the average)  find the sum of the numbers in the data set, and divide that sum by the number of numbers Median (the middle number)  order numbers from least to greatest, find the middle number [if there are two middle numbers, find their average] Mode  most occurring number (some data sets have more than one mode. Some have none. In 7th grade, students will learn how to compare two or more data sets by using the measures of central tendency AND measures of variability, such as Interquartile Range, and Mean Absolute Deviation (M.A.D.). Students looked at data distributions and applied a variety of ways to compare the data sets. We used the heights of athletes of different type of teams (gymnastics vs. volleyball & tennis vs. badminton). Resources:
AIM: How can we calculate the probability of multistep experiments? HW: 89 Practice (below) Announcement: Probability & Statistics Exam Wednesday  3/28/18 Simple/Compound Probability Probability Simulations Measures of Central Tendency Variability (M.A.D., IQR) Samples and Populations Comparing Samples Do Now: Is each equation true or false? Explain your reasoning. 1) 8=(8+8+8+8)÷3 2) (10+10+10+10+10)÷5=10 3) (6+4+6+4+6+4)÷6=5 Classwork: Yesterday we practiced creating sample spaces for multiple event scenarios (example: flipping a coin AND rolling a number). We used lists, tables, and tree diagrams. Today, we used those methods to create sample spaces and then calculate probabilities from those sample spaces. Resources:
College Access 4 All West Point Field Trip  Regularly scheduled classes not held
AIM: How can we find the probability of an event based on sample space? HW: 88 Practice (below) Announcement: Do Now: How many different meals are possible if each meal includes one main course, one side dish, and one drink? Main Course Side Dish Drink grilled chicken salad milk turkey apple sauce juice pasta salad water Classwork: Sometimes we need a systematic way to count the number of outcomes that are possible in a given situation. For example, suppose there are 3 people (A, B, and C) who want to run for the president of a club and 4 different people (1, 2, 3, and 4) who want to run for vice president of the club. We can use a tree, a table, or an ordered list to count how many different combinations are possible for a president to be paired with a vice president. With a tree, we can start with a branch for each of the people who want to be president. Then for each possible president, we add a branch for each possible vice president, for a total of 3(4) = 12 possible pairs. We can also start by counting vice presidents first and then adding a branch for each possible president, for a total of 3(4) = 12 possible pairs. A table can show the same result: 1 2 3 4 A  A, 1 A, 2 A, 3 A, 4 B  B, 1 B, 2 B, 3 B, 4 C  C, 1 C, 2 C, 3 C, 4 So does this ordered list: A1, A2, A3, A4, B1, B2, B3, B4, C1, C2, C3, C4 Resources:
AIM: How can we use simulation to estimate the probability of multistep events? Announcements: HW: 87 Worksheet (found below) Do Now: 1. What do you notice? [at least one thing] 2. What do you wonder? [at least one thing] Classwork: The more complex a situation is, the harder it can be to estimate the probability of a particular event happening. Welldesigned simulations are a way to estimate a probability in a complex situation, especially when it would be difficult or impossible to determine the probability from reasoning alone. To design a good simulation, we need to know something about the situation. For example, if we want to estimate the probability that it will rain every day for the next three days, we could look up the weather forecast for the next three days. Here is a table showing a weather forecast: today (Tuesday) Wednesday Thursday Friday probability of rain 0.2 0.4 0.5 0.9 We can set up a simulation to estimate the probability of rain each day with three bags. •In the first bag, we put 4 slips of paper that say “rain” and 6 that say “no rain.” •In the second bag, we put 5 slips of paper that say “rain” and 5 that say “no rain.” •In the third bag, we put 9 slips of paper that say “rain” and 1 that says “no rain.” Then we can select one slip of paper from each bag and record whether or not there was rain on all three days. If we repeat this experiment many times, we can estimate the probability that there will be rain on all three days by dividing the number of times all three slips said “rain” by the total number of times we performed the simulation. Resources:

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June 2018
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