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### How Businesses Use Regression Analysis Statistics

Regression analysis is a statistical tool used for the investigation of relationships between variables. Usually, the investigator seeks to ascertain the causal effect of one variable upon another — the

### Random Variables and Probability Distributions in Business Statistics

Random variables and probability distributions are two of the most important concepts in statistics. A random variableassigns unique numerical values to the outcomes of a

### Explore Hypothesis Testing in Business Statistics

In statistics, hypothesis testing refers to the process of choosing between competing hypotheses about a probability distribution, based on observed data from the distribution. It's a core topic and a

### 3 Ways to Describe Populations and Samples in Business Statistics

When you're working with populations and samples (a subset of a population) in business statistics, you can use three common types of measures to describe the data set: central tendency, dispersion, and

### Understand Sampling Distributions in Business Statistics

In statistics, sampling distributions are the probability distributions of any given statistic based on a random sample, and are important because they provide a major simplification on the route to statistical

### Business Statistics For Dummies Cheat Sheet

Statistics make it possible to analyze real-world business problems with actual data so that you can determine if a marketing strategy is really working, how much a company should charge for its products

### Business Statistics: Use Regression Analysis to Determine Validity of Relationships

Regression analysis is one of the most important statistical techniques for business applications. It's a statistical methodology that helps estimate the strength and direction of the relationship between

### Business Statistics: Modeling Asset Returns with Normal Distribution

Market participants — equity analysts, risk managers, portfolio managers, traders, and economists — must be able to accurately measure and model the risk and return of financial assets. As a starting point

### Business Statistics: Assess Financial Risk with the VaR Methodology

In the field of risk management, you can measure the risk of a portfolio with the Value at Risk (VaR) methodology. The standard VaR model (known as the

### Applying Hypothesis Testing in Business Statistics

Hypothesis testing isn't just for population means and standard deviations. You can use this procedure to test many different kinds of propositions. For example, a jury trial can be seen as a hypothesis

### Business Statistics: Is Forecasting Market Prices Truly Achievable?

Depending on your school of thought, forecasting market prices can be either a waste of time or the key to financial success. Either way, knowing about each camp is useful as you learn about business statistics

### Determine the Relationship between Variables Using Covariance and Correlation

You can determine the relationship between two variables with two measures of association: covariance and correlation. For example, if an investor wants to understand the risk of a portfolio of stocks,

### Draw Conclusions about a Population Using Confidence Intervals and Hypothesis Testing

When drawing conclusions about a population from randomly chosen samples (a process called statistical inference), you can use two methods: confidence intervals and hypothesis testing.

### How to Calculate the Relative Frequency of a Class

A frequency distribution shows the number of elements in a data set that belong to each class. In a relative frequency distribution, the value assigned to each class is the

### How to Find the Cumulative Frequency of a Class and All Prior Classes

Cumulative frequency refers to the total frequency of a given class and all prior classes in a graph. For example, say that you have researched the price of gas at several gas stations in your area, and

### How to Find the Weighted Arithmetic Mean of a Data Set

Sometimes a data set contains a large number of repeated values. In these situations, you can simplify the process of computing the mean by using weights

### How to Find the Weighted Geometric Mean of a Data Set

When a data set contains a large number of repeated values, you can simplify the process of computing the mean by using weights — the frequencies of a value in a sample or a population. You can then compute

### How to Locate a Value in a Data Set Using Quartiles

Quartiles split up a data set into four equal parts, each consisting of 25 percent of the sorted values in the data set. Quartiles are related to percentiles like so:

### How to Use Relative Variation to Find the Uncertainty Associated with a Data Set

Relative variation refers to the spread of a sample or a population as a proportion of the mean. Relative variation is useful because it can be expressed as a percentage, and is independent of the units

### How to Measure the Covariance and Correlation of Data Samples

When comparing data samples from different populations, two of the most popular measures of association are covariance and correlation. Covariance and correlation show that variables can have a positive

### The Difference between Mutually Exclusive and Independent Events

An event is one possible outcome of a random experiment. Events may sometimes be related to each other. Two key ways in which events may be related are known as mutually exclusive and independent.

### How to Find Unconditional, or Marginal, Probabilities

An unconditional, or marginal, probability is one where the events (possible outcomes) are independent of each other. When you create a joint probability table

### How to Compute Probabilities Using the Addition Rule

You use the addition rule to compute the probability of the union of two events. Mathematically speaking, for events Aand B, the addition rule states that

### How to Compute Probabilities by Following the Complement Rule

Two events are said to be complements if they are mutually exclusive and their union equals the entire sample space. This is represented by the complement rule, which is expressed as follows:

### How to Use Combinations to Factor Binomial Probabilities

In the binomial formula, you use the combinations formula to count the number of combinations that can be created when choosing x objects from a set of

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