Help
Options
Didn't know it?
click below
click below
Knew it?
click below
click below
Don't Know
Remaining cards (0)
Know
retry
shuffle
restart
0:00
Embed Code - If you would like this activity on your web page, copy the script below and paste it into your web page.
Normal Size Small Size show me how
Normal Size Small Size show me how
Exam 2 Definitions
Introduction to Statistics- Chapters 3 and 4
| Question | Answer |
|---|---|
| Probability Experiment | An action, or trail, through which specific results(counts, measurement, or responses) are obtained |
| Outcome | The result of a single trial in a probability experiment |
| Sample Space | The set of all possible outcomes of a probability experiment |
| Event | Consists of one or more outcomes and is a subset of the sample space |
| Simple Event | An event that consists of a single outcome |
| When is an event simple vs. not simple? | An event that consists of more than one outcome is not a simple event, an event that has one outcome is a simple event |
| Example of simple event | Tossing heads and rolling a three |
| Example of a non-simple event | Tossing heads and rolling an even number |
| How can the fundamental Counting Principle be used? | The Fundamental Counting Principle can be used to find the number of ways tow or more events can occur in sequence |
| Fundamental Counting Principle | If one event can occur in m ways and a second event can occur in n ways, then the number of ways the two events can occur in sequence is m(n) This rule can be extended to any number of events occuring in sequence |
| Three types of probability | Classical(or Theoretical) Empirical(or Experimental) Subjective |
| When is classical probability used? | It is used when each outcome is a sample space is equally |
| What is empirical probability based on? | It is based on observations obtained from probability experiments |
| What is the law of large numbers | As an experiment is repeated over and over, the empirical probability of an event approaches the theoretical(actual) probability of the event |
| What is subjective probability? | Intuition, educated guesses, estimates |
| What is the range of probabilities rule? | The probability of event E is between 0 and 1, inclusive |
| Complementary of event E definition | The set of all outcomes in a sample space that are not included in event E |
| Conditional Probability definition | The probability of an event occurring, given that another event has already occurred |
| When are two events independent? | Two events are independent when the occurrence of one of the events does not affect the probability of the occurrence of the other event |
| When are two events dependent? | When the occurrence of one event affects the probability of the occurrence of the second event |
| When can you use the multiplication rule? | To find the probability of two events occurring in sequence |
| What does it mean to say that two events are mutually exclusive? | A and B cannot occur at the same time That A and B have no outcomes in common |
| What is the addition rule? | An equation that can be used to find the probability of mutually exclusive events |
| Why is the addition rule used? | To find the probability of at least two event occurring |
| What is a permutation? | An ordered arrangement of objects. The number of different permutation of n distinct objects is n! |
| Permutation of n objects taken r at a time is used when you want to... | Choose some of the objects in a group and put them in order |
| Combinations description | The number of combinations of r objects selected from a group of n objects without regard to order |
| What is distinguishable permutations used to find? | The number of distinguishable permutations possible, number of ways to order a group |
| Random variable definition | A random variable x represents a value associated with each outcome of a probability experiment |
| Give an example of x when x is a random variable | number of sales calls a salesperson makes in one day Hours spent on slaves calls in one day |
| What are the two types of random variables | discrete and continuous |
| When is a random variable discrete? | When it has a finite or countable number of possible outcomes that can be listed |
| When is a random variable continuous? | When it has an uncountable number of possible outcomes, represented by an interval on a number line |
| Example of a discrete random variable | Number of sales calls a salesperson makes in one day |
| Example of a continuous random variable | Hours spent on sales calls in one day Height |
| What does a discrete probability distribution do? | It lists each possible value the random variable can assume, together with its probability |
| What conditions must a discrete probability variable satisfy? | The probability of each value of the discrete random variable is between 0 and 1, inclusive The sum of all probabilities is 1 |
| How to construct a discrete probability distribution | Make a frequency distribution for the possible outcomes(1) Find the sum of the frequencies(2) and probability of each possible outcome(3) check that it satisfies the conditions of a discrete probability variable(4) |
| What does the mean of a random variable represent? | The "theoretical average" of a probability experiment and sometimes is not a possible outcome |
| What happens to the mean of a random variable the more times an experiment is performed? | The mean of all the outcomes would be closer to the mean of a random variable |
| What is a binomial experiment? | It is a type of probability experiment |
| What are the conditions of a binomial experiment that must be satisfy? | The experiment has a set number of trials, where each trial is independent, there are only two possible outcomes of interest, the probability of success is the same for each trial, and the random varible x counts the number of successful trials |
| What does n stand for in the binomial experiment equation? | The number of trials |
| What does p stand for in the binomial experiment equation? | The probability of success in a single trial |
| What does q stand for in the binomial experiment equation? | The probability of failure in a single trial |
| What does x stand for in the binomial experiment equation? | The random variable represents a count of the number of successes in n trials x= 1, 2, 3, ..., n |
| How to find q in relation to p | q=1-p |
Created by:
user-1976060