Course title

Pre-requisite

Course description

Introduction to Data Science and Statistics

Hillsdale High School

†††††††††††††††††2021-22

†

Course Description:

†

This course provides a basic introduction to statistics and data analysis.† Statistics is the study of variation. It is the tools and concepts that have been developed; over centuries; to help us understand variation.† We start with how we take variation in the world and turn it into data.† We will then use the statistical tools and concepts to explore variation and patterns within our data; construct models for our data and finally evaluate how well our models explained the data.

†

At the end of this course; students should:

1. Understand basic statistical concepts; and be able to use these concepts to make sense of new situations.

2. Be prepared to learn more advanced statistical concepts in the future.

3. Be able to do basic data analysis using R.

Text and Materials

†

1. Interactive Digital Textbook: Available in Canvas

†

2. Printed Cheat Sheet

†

3. Class Notebook: You will need a class notebook for this class.† You should use this notebook to take all notes related to this class; both in lectures and while working through the online homework materials.

†

Classwork:

†Students will be frequently asked to discuss ideas and attempt questions in class. Missing class frequently and not attempting to answer questions will result in low classwork scores. In order to assure that all students develop their ability to verbally communicate statistical concepts.†

Assessment

Independent Evaluation50%

-Readings (notes)

-Text questions

-Assignments

-Assessments

Collaborative Evaluation50%

-Discussions/ Engagement

-Jupyter Notebooks

-Projects

Quizzes will be given during class and may include both multiple choice and short answer questions. Quizzes will be taken on the computer (this means there is going to be coding involved). You may use your official class notebook during quizzes. Quizzes are cumulative; which means they can cover all homework assignments that are due prior to the quiz.

†

Student Learning Outcomes

†

General Outcomes

Students will be able to understand and apply basic analytic methods including:

†

1. Selection of an analytic strategy appropriate to the data at hand

2. Data organization and entry using standardized statistical packages (R)

3. Implementation of data analysis by hand and via standardized statistical packages

4. Checking for violation of statistical assumptions

5. Interpretation of output/results from analysis

6. Appropriate reporting results (written; tabular; graphical)

†

Specific Outcomes

Students will be able to:

1. Describe the nature of descriptive statistics

2. Explain the basic characteristics of samples and populations; statistics and parameters

3. Identify and understand the differences among types of variable (explanatory and outcome variable) and levels of measurement (categorical and quantitative)

4. Use statistical notation to model data

5. Use both tabular and graphical methods to effectively organize and present data

6. Describe; calculate and discuss the uses of measures of central tendency and variability

7. Identify how central tendency; variability; and shape of distribution are related

8. Be familiar with the normal curve; derived scores; and basic probabilities

9. Understand how to describe bivariate data (correlation and regression). † † † † † † † † † † † † † † † † † † † † † † † † † † † † † † † † † † † † ††

Describe the basic characteristics of parametric and nonparametric statisticsExplain the use; assumptions; and basic processes involved in the different parametric and nonparametric procedures used by psychologists

1. a.† † † † † describe the type of data required for each strategy

   b.† † † † † articulate strengths and weaknesses of each strategy

   c.† † † † † discuss basic assumptions associated with each strategy and how to check for (and deal with) violations of these assumptions

   3. Be familiar with basic probability concepts and the steps involved in hypothesis testing

   a.† † † † † discuss the concept of statistical significance (in the context of probability and sampling distributions) versus practical significance (effect size)

   b.† † † † † distinguish among type I and type II errors

   4. †Analyze data; interpret results; and report findings for each individual analytic strategy

   5. Utilize critical thinking skills

   a.† † † † † evaluate the nature of their data

   b.† † † † † determine which analytic strategy is appropriate

   c.† † † † † determine which assumptions must be checked

   d.†engage in creative thinking as they select among different analytic methods (each of which may be used to analyze the same data set)

   e. present their findings in an intelligible and interesting manner

School country

School state

School city

High school

School / district Address

School zip code

Requested competency code

Date submitted

Approved

Approved competency code

• MTHA
• 4 years of Math

Approved date

Online / Virtual