Exam 6: Continuous Distributions

A correction for continuity must be made when approximating the binomial distribution problems using a normal distribution.

(True/False)

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Question 101

The exponential distribution is a continuous distribution that is closely related to the Poisson distribution.

(True/False)

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Question 102

Let z be a normal random variable with mean 0 and standard deviation 1.What is P(z > 2.4)?

(Multiple Choice)

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Question 103

The area under the standard normal distribution between -1 and 1 is twice the area between 0 and 1.

(True/False)

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Question 104

Suppose the total time to fill a routine prescription at a local pharmacy averages 35 minutes starting from the time the physician places the order to the time it is dispensed.Assume the standard deviation is 11 minutes and the z score is 0.What is x?

(Multiple Choice)

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Question 105

Showing 101 - 105 of 105

A correction for continuity must be made when approximating the binomial distribution problems using a normal distribution.

The exponential distribution is a continuous distribution that is closely related to the Poisson distribution.

Let z be a normal random variable with mean 0 and standard deviation 1.What is P(z > 2.4)?

The area under the standard normal distribution between -1 and 1 is twice the area between 0 and 1.

Suppose the total time to fill a routine prescription at a local pharmacy averages 35 minutes starting from the time the physician places the order to the time it is dispensed.Assume the standard deviation is 11 minutes and the z score is 0.What is x?

Introduction to Statistics and Business Analytics

Visualizing Data With Charts and Graphs

Descriptive Statistics

Probability

Discrete Distributions

Sampling and Sampling Distributions

Statistical Inference: Estimation for Single Populations

Statistical Inference: Hypothesis Testing for Single Populations

Statistical Inferences About Two Populations

Analysis of Variance and Design of Experiments

Simple Regression Analysis and Correlation

Multiple Regression Analysis

Building Multiple Regression Models

Time-Series Forecasting and Index Numbers

Analysis of Categorical Data

Nonparametric Statistics

Statistical Quality Control

Decision Analysis

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