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✍️ Free Response Questions (FRQs)
👆 Unit 1 - Exploring One-Variable Data
✌️ Unit 2 - Exploring Two-Variable Data
🔎 Unit 3 - Collecting Data
🎲 Unit 4 - Probability, Random Variables, and Probability Distributions
📊 Unit 5 - Sampling Distributions
⚖️ Unit 6 - Inference for Categorical Data: Proportions
😼 Unit 7 - Inference for Qualitative Data: Means
✳️ Unit 8 Inference for Categorical Data: Chi-Square
📈 Unit 9 - Inference for Quantitative Data: Slopes
🧐 Multiple Choice Questions (MCQs)
✏️ Blogs
Best Quizlet Decks for AP Statistics
- Unit 1 Key Terms (15-23%): Exploring One-Variable Data
- Unit 2 Key Terms (5-7%): Exploring Two-Variable Data
- Unit 3 Key Terms (12-15%): Collecting Data
- Unit 4 Key Terms (10-20%): Probability, Random Variables, and Probability Distributions
- Unit 5 Key Terms (7-12%): Sampling Distributions
- Unit 6 Key Terms (12-15%): Inference for Categorical Data: Proportions
- Unit 7 Key Terms (10-18%): Inference for Quantitative Data: Means
- Unit 8 Key Terms (2-5%): Inference for Categorical Data: Chi-Squared
- Unit 9 Key Terms (2-5%): Inference for Quantitative Data: Slopes
- Closing Thoughts
4.9 Combining Random Variables
#exploringdata
#anticipatingpatterns
⏱️ 2 min read
written by
kanya shah
June 3, 2020
This section is about transforming random variables by adding/subtracting or multiplying/dividing by a constant. Make sure you know how to combine random variables to calculate and interpret the mean and standard deviation.
Linear Transformations of a Random Variable
Y = a + BX
Adding/Subtracting by a constant affects measures of center and location but does NOT affect variability or the shape of a distribution. Multiplying or dividing by a constant affects center, location, and variability measures but won’t change the shape of a distribution.
How to Find the Expected Value of the Sum/Difference of Two Random Variables
Sum: For any two random variables X and Y, if S = X + Y, the mean of S is meanS= meanX + meanY. Put simply, the mean of the sum of two random variables is equal to the sum of their means.
Difference: For any two random variables X and Y, if D = X - Y, the mean of D is meanD= meanX - meanY. The mean of the difference of two random variables is equal to the difference of their means. The order of subtraction is important.
Independent Random Variables: If knowing the value of X does not help us predict the value of X, then X and Y are independent random variables.
Standard Deviation of the Sum/Difference of Two Independent Random Variables
Sum: For any two independent random variables X and Y, if S = X + Y, the variance of S is SD^2= (X+Y)^2 . To find the standard deviation, take the square root of the variance formula: SD = sqrt(SDX^2 + SDY^2).
Standard deviations do not add; use the formula or your calculator.
Difference: For any two independent random variables X and Y, if D = X - Y, the variance of D is D^2= (X-Y)^2=x2+Y2. To find the standard deviation, take the square root of the variance formula: D=sqrt(x2+Y2). Notice that you are NOT subtracting the variances (or the standard deviation in the latter formula).
🎥Watch: AP Stats - Combining Random Variables
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