The following is what you will complete during my absence.
1) The substitute teacher will hand out the answer key to the homework. Look over it as a group. If there are any problems or questions try to resolve them as a group. I also linked the answer key below for anyone who is absent.
Answer Key - HW - pgs. 129-133 (5-15 odd, 25, 27, 28, 38, 39, 41)
2) The substitute should also handout a classwork worksheet that can be completed with your Syracuse Partner. Put both (all) of your names on your worksheet/loose-leaf. Activity 14-8, 14-10 and 14-11 should be completed on a loose leaf sheet of paper. Place completed work in the tray in the front of the room. I have linked the classwork below for anyone who is absent.
CW - The Normal Distribution
3) Upon completing the classwork you can start the homework which will be Tuesday October 7th.:
HW - Complete pgs. 129-133 (17, 29, 43, 45, 47)
Read Chapter 7 (146-160)
Tuesday, September 30, 2014
Monday, September 29, 2014
The Normal Model (cont.)
In class students continued working with the normal model to find normal percentiles (NormCDF in calculator) and percentiles to z-scores (InvNorm in calculator).
The homework is listed below and the notes are attached.
Notes - Normal Percentiles
HW - pgs. 129-131 (5-15 odd, 25, 27, 38, 39, 41)
- Read Chapter 7 by Tuesday 10/7
The homework is listed below and the notes are attached.
Notes - Normal Percentiles
HW - pgs. 129-131 (5-15 odd, 25, 27, 38, 39, 41)
- Read Chapter 7 by Tuesday 10/7
Wednesday, September 24, 2014
The Normal Distribution
In class students took Quiz #2 on Categorical and Quantitative Data. Afterwards, students were introduced to their first model in the course - The Normal Model. The Normal Model will be used to talk about populations that are "normally distributed," meaning the shape of the distribution is unimodal and roughly symmetric.
Students learned about the 68-95-99.7 rule which states that for a normal population 68% of the data lies within one standard deviation(σ) of the mean (μ), 95% of the data lies within 2 standard deviations of the mean and 99.7% of the data lies within 3 standard deviations of the mean.
*Anything beyond 3 standard deviations of the mean is unusual.
The notes are attached. The only homework is to get the AP Statistics Contract signed which I have linked below.
Notes - The Normal Model
AP Statistics Contract
Students learned about the 68-95-99.7 rule which states that for a normal population 68% of the data lies within one standard deviation(σ) of the mean (μ), 95% of the data lies within 2 standard deviations of the mean and 99.7% of the data lies within 3 standard deviations of the mean.
*Anything beyond 3 standard deviations of the mean is unusual.
The notes are attached. The only homework is to get the AP Statistics Contract signed which I have linked below.
Notes - The Normal Model
AP Statistics Contract
Monday, September 22, 2014
Z-Scores
In class students were introduced to z-scores which are number of standard deviations away from the mean. We now have a way of comparing apples to oranges. How far away datum is from the mean tells us whether something is unusual or not. Standardized tests such as the SATs and ACTs are scored based upon z-scores.
The notes are attached and the homework is listed below.
Notes - Z Scores
HW - Read pgs. 111-126
Study for Quiz #2
Investigative Task #3 - Auto Safety - Due 9/24
The notes are attached and the homework is listed below.
Notes - Z Scores
HW - Read pgs. 111-126
Study for Quiz #2
Investigative Task #3 - Auto Safety - Due 9/24
Thursday, September 18, 2014
Comparing Distributions
In class students learned the various ways in which to compare distributions using the following:
1) Histograms
2) Back-to-Back Stemplots
*3) Boxplots (2 or more distributions)
In class we spent time learning how to draw boxplots using the 5 number summary. Students should be conscious of outliers (1.5 x IQR ± the quartiles) and extreme outliers (3 x IQR ± the quartiles).
The homework is listed below. The notes and Investigative Task #3, due Wednesday 9/24, are attached.
Notes - Comparing Distributions
Investigative Task #3 - Auto Safety
HW - complete pgs. 99-101 (26-29, 34)
read pgs. 104-109
**Quiz on Quantitative data Wednesday 9/24**
1) Histograms
2) Back-to-Back Stemplots
*3) Boxplots (2 or more distributions)
In class we spent time learning how to draw boxplots using the 5 number summary. Students should be conscious of outliers (1.5 x IQR ± the quartiles) and extreme outliers (3 x IQR ± the quartiles).
The homework is listed below. The notes and Investigative Task #3, due Wednesday 9/24, are attached.
Notes - Comparing Distributions
Investigative Task #3 - Auto Safety
HW - complete pgs. 99-101 (26-29, 34)
read pgs. 104-109
**Quiz on Quantitative data Wednesday 9/24**
Tuesday, September 16, 2014
The 5 Number Summary and Symmetric Distributions
In class students learned how to use the 5 number summary (min, Q1, med., Q2, max) to describe a asymmetric distribution. Students also learned how to find the Interquartile Range (IQR) = Q3 - Q1.
Afterwards, students learned about symmetric distributions. For symmetric distributions we use the mean and standard deviation to describe the center and spread, respectively.
The notes and homework are attached.
Notes - Symmetric Distribution
HW - Complete Investigative Task #2 (attached below)
Read Chapter 5 - Comparing Distributions
Investigative Task #2 - Dollar for Scholars
Afterwards, students learned about symmetric distributions. For symmetric distributions we use the mean and standard deviation to describe the center and spread, respectively.
The notes and homework are attached.
Notes - Symmetric Distribution
HW - Complete Investigative Task #2 (attached below)
Read Chapter 5 - Comparing Distributions
Investigative Task #2 - Dollar for Scholars
Monday, September 15, 2014
Quantitative Data
In class students took their first quiz on categorical data. Afterwards, students were introduced to quantitative data and the 4 distributions used to display quantitative data:
1. Histograms
2. Stem and Leaf Plots
3. Dot Plots
*4. Box Plots (used to compare 2 or more distributions)
Students also learned how describe quantitative distributions:
1. Shape - a. symmetry/b. modes
2. Center - a. mean/ b. median
3.Spread - a. Standard Deviation/b. Interquartile Range (IQR)
The notes are attached and the homework is listed below.
Notes - Quantitative Data
HW - pgs. 72-73 (7-15 odd)
1. Histograms
2. Stem and Leaf Plots
3. Dot Plots
*4. Box Plots (used to compare 2 or more distributions)
Students also learned how describe quantitative distributions:
1. Shape - a. symmetry/b. modes
2. Center - a. mean/ b. median
3.Spread - a. Standard Deviation/b. Interquartile Range (IQR)
The notes are attached and the homework is listed below.
Notes - Quantitative Data
HW - pgs. 72-73 (7-15 odd)
Wednesday, September 10, 2014
Review - Catagorical Data/Contingency Tables
In class we reviewed the material on categorical data and contingency tables for Quiz #1 which will be administered on Friday. Afterwards, students completed Groupwork Activity #1.
For homework, study for the Quiz #1, complete Investigative Task #1 and read Chapter 4.
For homework, study for the Quiz #1, complete Investigative Task #1 and read Chapter 4.
Monday, September 8, 2014
Contingency Tables
In class students were introduced to contingency tables that showed the interaction between 2 variables. We can use a side-by-side bar chart, segmented bar graph or comparative pie charts to display the data.
Students were also introduced to marginal and conditional distributions. Marginal distribution is the distribution along one variable. Conditional distribution is the distribution of one variable along another.
If the conditional distribution = marginal distribution; we say the variables are independent. If conditional distribution ≠ marginal distribution we say there is an association between the two variables.
The notes are attached and the homework is listed below.
Notes - Contingency Table
HW - pgs. 40-43 (21-35 odd)
Due Friday:
Investigative Task #1 - Race and the Death Penalty
Read Chapter 4 - Displaying and Summarizing Quantitative Data
Students were also introduced to marginal and conditional distributions. Marginal distribution is the distribution along one variable. Conditional distribution is the distribution of one variable along another.
If the conditional distribution = marginal distribution; we say the variables are independent. If conditional distribution ≠ marginal distribution we say there is an association between the two variables.
The notes are attached and the homework is listed below.
Notes - Contingency Table
HW - pgs. 40-43 (21-35 odd)
Due Friday:
Investigative Task #1 - Race and the Death Penalty
Read Chapter 4 - Displaying and Summarizing Quantitative Data
Thursday, September 4, 2014
Introduction to Statistics/Categorical Data Displays
In class students were introduced to the world of statistics. We also collected some class data and created some categorical data displays (bar graphs/pie charts).
The homework is listed below and the notes are attached.
Notes - Intro to Stats/Categorical Data Displays
HW - Read Chapter 3
- Complete pgs. 38-39 (5-15 odd)
P.S. - Did I spell "Categorical" as "Catagorical" during the entire period and nobody corrected me?
The homework is listed below and the notes are attached.
Notes - Intro to Stats/Categorical Data Displays
HW - Read Chapter 3
- Complete pgs. 38-39 (5-15 odd)
P.S. - Did I spell "Categorical" as "Catagorical" during the entire period and nobody corrected me?
Tuesday, September 2, 2014
First Day!
Welcome Back! I enjoyed meeting all of you today and getting back into the swing of things. Below, I have attached the course syllabus.
Statistics - Syllabus
HW - Signed Syllabus
- Finish Summer Packet
Statistics - Syllabus
HW - Signed Syllabus
- Finish Summer Packet
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