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Applied Statistics

Applied Statistics:This course will focus on topics in statistics with an emphasis on their practical applications in social media, sports, medicine, research, and practically any field that interests you. Have you ever wondered if having a Facebook page makes you more likely to Tweet? Do White Plains High School students prefer orange or black and does gender influence the response? Is there a home field advantage in the NFL? Does the amount of snow needed to close school vary in New York State? Can polyurethane suites make you swim faster? These are the types of questions students will explore in this course. Topics include categorical and numerical data, paired data, measure of variability, normal distribution, confidence intervals, non-linear models, and counting rules. There will be an emphasis on exploration of major concepts through hands-on data collection and analysis. The final exam is a choice between a departmental exam or final project.

 


 Please note that the timelines listed below are a guide. Teachers modify their pacing based on student needs in order to ensure concept mastery.

Unit 1

Quantitative Data

Sept - Nov

1.1

What is Quantitative and Categorical Data?

1.2

How do we construct a Histogram?

1.3

How do we create and interpret Dot Plots?

1.4

How do we calculate the Mean, Median, Mode and Range in a data set?

1.5

How do determine whether the shape of a graph has Symmetry or Skewness?

1.6

When do we use the Mean vs. the Median in a data set?

1.7

How do we create a Box Plot?

1.8

How do we find Outliers?

 End of Quarter 1

1.9

How do we calculate the Standard Deviation in a data set?

1.10

How do we work with data that can be represented by a Normal Curve?

1.11

How do we estimate the area under the Normal Curve Using Z-scores?

Unit 2

Probability

November - February

2.1

How do we intersections and unions of sets?

2.2

How do we work with Events as Subsets of a Sample Space?

2.3

How do we calculate the probability of Independent and Dependent Events?

2.4

How do we calculate Conditional Probabilities?

2.5

What is the relationship between Conditional Probability and Independent Events?

2.6

How do we apply the Addition Rule for Probability?

 End of Quarter 2

2.8

How do we calculate a Permutation?

2.9

How do we calculate the probability of a Permutation?

2.10

How do we calculate a Combination?

2.11

How do we calculate the probability of a Combination?

Unit 3

Categorical Data

March

3.1

How do perform Statistical Analysis on Categorical Data?

3.2

How we summarize Categorical Data using tables?

3.3

How do we create and interpret Bar Graphs and Pie Charts?

Unit 4

Bivariate Data

March - April

4.1

How do create and interpret a Linear Regression Model?

 End of Quarter 3

4.2

How do we calculate and interpret the Correlation Coefficient?

Unit 5

Sampling and Experimental Designs

April

5.1

How do we collect a Random sample from a Population?

5.2

How do we design a Random Experiment?

Unit 6

Inferences

April - May

6.1

How do we construct and interpret a Confidence Interval?

 

6.2

How do we perform a T-Test for a Proportion?

 

6.3

How do we perform a T-Test for a Mean?

 

6.4

How do we perform a Chi-Square Test?

 

 Culminating Research Project