# AP stats summer assignment

In order to complete the AP Stats summer assignment, you will need to have a firm understanding of probability and how it is used in statistical analysis. In this blog post I will provide a brief overview on what probability is and introduce some basic concepts in statistics.  The first thing we need to establish in probability is that there are two types of events: dependent and independent. Seek our AP stats summer assignment today. ORDER NOW.

AP stats summer assignment

Dependent events occur because one event causes another event, which means these can not be predicted with certainty as they don’t happen at random like independent events do. For ,example if someone flips a coin three times then the number of heads should always equal the number of tails; but if they flip it four times then those numbers can differ from each other by chance alone .

## What is AP stats?

AP Statistics is a course designed to teach students the statistical reasoning needed in their future career. The course focuses on developing students’ statistical reasoning skills and fostering their ability to assess real-world data and draw conclusions from it.

## What is the importance of learning AP stats?

The foundation for this course is not memorizing formulas or plugging in numbers, but rather learning to think like a statistician. As there are no right answers, the course allows students to develop their own sense of confidence through experience and success with statistical reasoning, problem solving, critical thinking, and communication.

## What is the program structure?

The course is divided into two sections: a) the first focuses on statistical reasoning and quantitative literacy b) the second part of the course focuses on statistical techniques

There are 4 units:

### Unit 1: Exploring Data and Statistical Inference – Quantitative Literacy

The focus of this unit is descriptive and inferential statistics. Topics include: collecting, organizing, and depicting data; measures of central tendency and variability; graphical displays; describing relationships in bivariate data; and estimation.

### Unit 2: Statistical Inference – Probability and Distributions

The focus of this unit is probability in both discrete and continuous cases. Topics include: basic concepts in probability; conditional probability; the rules of counting; permutations and combinations; tree diagrams; distribution functions for discrete, continuous data; and the normal distribution.

### Unit 3: Inferential statistics

Planning and Conducting Experiments, Surveys, and Observational Studies – Statistical Techniques. Topics include: sampling; hypothesis testing; estimation; confidence intervals; power and sample size determination; randomization.

### Unit 4: Drawing Conclusions from Data – Statistical Techniques

This unit entails inferential statistics. Topics include: sampling; hypothesis testing; estimation; confidence intervals; power and sample size determination; randomization.

## Course Assessment

The grade distribution in AP Statistics is relatively straightforward, with 60 percent of the overall score based on the final exams and 40npercent on assignments and random assessment tests.

## What are the prerequisites?

There are not any; however, AP Statistics is an introductory course and it does require students to be comfortable with mathematics.  It would be recommended that students have taken Algebra 1 in high school or its equivalent course.

## What are the projects?

There are two major projects in AP Statistics each year – either the stem-and-leaf . The first, which is worth 25 percent of the AP exam.

For the stem-and-leaf plot project, students collect and organize data from a survey. They create a stem-and-leaf plot to summarize the behaviour of their sample population, then use that to make inferences about the population. The second project, which is worth 25 percent of the AP exam, includes two components: sampling statistics and experimental design.

What are some extra materials I can use?  If there is time left over after completing all projects/assignments , it would be beneficial for students to practice using R for statistics, an open-source statistical software.  You may also want to have use Excel if you are not already familiar with it in your class. You can also access direct tutorials on the statistical software at https://assignmentsguru.com/.

## What are the grading standards?

AP statistics is graded on a curve. Each AP instructor sets their own standards for what level the class needs to perform at in order to attain a certain score.

## Math review for statistics

Let us review a few concepts in AP stats.

### Regression and Correlation

The focus of this unit is estimation, prediction, hypothesis testing, and correlation. Topics include: simple linear regression; correlation; multiple regression; residual plots; causal relationships; correlation scatterplots; partial correlations; prediction intervals.

#### What is regression?

Correlation is a relationship between two variables that measures their linear dependence. Regression carries the idea of dependence further by describing how a change in one variable can predict a value of another variable.

What is correlation? When two things vary together in a way that is related to , there is a correlation. For example, your height might be correlated with the number of lice you have. As one goes up, so does the other. The value of “r” that is close to 1 means that there’s a strong positive linear relationship between two variables; the value of “r” that is close means that there’s a strong negative linear relationship between two variables.

##### Simple linear regression

Simpel linear regression is the process of finding a line that best fits some data. This line can be used to make predictions about unknown values.

What are residual plots? Why are they useful?    Residuals are differences between predicted and actual values. For example, if you predict temperature as and it is , then your residual would be . A residual plot shows the predictions and residuals on the same x-y axis.

##### What is multiple regression?

When you have more than one predictor variable, you use the process of multiple regression. In this case, your prediction equation contains an additional term: the product of two or more predictor variables….

Scatter plots

Scatterplots show relationships between two variables. The relationship is usually linear, which means that the points appear to be “stacked” on top of each other and form a straight line.

## Probability – Quantitative Literacy

### Collecting, organizing, and depicting data

What is a data set? In statistics, a data set is a collection of individual pieces of data. For example, you might have collected the following temperature readings from five different cities in California over three days: 28, 32, 26, 31, 36.

In Excel or another spreadsheet program, generate a frequency distribution. The first step is to enter the data into an Excel spreadsheet; you can find our example data at assignmentguru.com. …

### Measures of central tendency and variability

The two measures of central tendency are the mean and the median.

The standard deviation is a measure of variability, or how spread out the data values are. A low standard deviation indicates that the data is very close to the mean; this means that there isn’t much. A high standard deviation indicates that the data is spread out from the mean.

### Probability distributions

A probability distribution is a table or an equation that shows the likelihood of certain outcomes.  For example, you might see something like this:

This is one way to show the probability distribution for rolling three dice (D-Day game). If I wanted to find the chance of rolling double sixes, I would just look at the double sixes section of this table.

There are two categories of probability distributions: Discrete and continuous types.

Discrete distributions include;

#### Bernoulli distribution

This is the probability distribution for one (or two) trial event. The experiments are independent; that is, the outcome of one experiment does not affect the outcome of any other experiment.

#### Binomial distribution

This is the probability distribution for a binomial experiment. That is, an experiment that consists of “n” trials and has only two possible outcomes for each trial (usually called success and failure).

#### Poisson distribution

This is the probability distribution for an experiment with a certain number of independent events that happen in a given time or space, such as earthquakes per year or telephone calls arriving at an exchange per hour.

Continuous distributions include;

#### Normal distribution

This is the most widely used continuous probability distribution. It gives us a gaussian bell curve for the given data.

#### t-distribution

This is important to know because it describes how likely you are to get different types of scores when doing multiple tests on the same item set. If you want to find out more, check out this website https://assignmentsguru.com/.

#### Chi-square distribution

This is the probability distribution for a chi-square test. This shows us how likely it is to get different numbers of frequencies when we have certain distributions in data sets.