Assignment 2
... signatures, but on many sheets a smaller number of signatures had been collected. The numbers of signatures per sheet were counted on a random sample of 50 sheets, with the results shown below. Number of ...
... signatures, but on many sheets a smaller number of signatures had been collected. The numbers of signatures per sheet were counted on a random sample of 50 sheets, with the results shown below. Number of ...
Lesson 8.1 Estimation µ when σ is Known Notes
... zc = critical value for confidence level c based on the standard normal distribution. Example 3: Julia enjoys jogging. She has been jogging over a period of several years during which time her physical condition has remained constantly good. Usually, she jogs 2 miles per day. The standard deviation ...
... zc = critical value for confidence level c based on the standard normal distribution. Example 3: Julia enjoys jogging. She has been jogging over a period of several years during which time her physical condition has remained constantly good. Usually, she jogs 2 miles per day. The standard deviation ...
Sample Mean and Standardization notes
... - doesn’t tell you the area under the curve (probability) 4. to find actual probability between two points could integrate function and solve over interval (but this is too cumbersome)-For MATH 115B-we use integrating excel. Z score (a.k.a., standardized score) translates “raw scores” into a sta ...
... - doesn’t tell you the area under the curve (probability) 4. to find actual probability between two points could integrate function and solve over interval (but this is too cumbersome)-For MATH 115B-we use integrating excel. Z score (a.k.a., standardized score) translates “raw scores” into a sta ...
Introduction to Hypothesis Testing
... , thus x L m z a n n By increasing the sample size the standard deviation of the sampling distribution of the mean decreases. Thus, x Ldecreases. ...
... , thus x L m z a n n By increasing the sample size the standard deviation of the sampling distribution of the mean decreases. Thus, x Ldecreases. ...
Lecture 14 - Probability and CLT
... Z = a value from the normal distribution S = standard error **Note: values for Z vary depending on the probability level. Z = 1.96 (you can use a value of 2 for quick approximations) for 95% confidence limits. For small samples (n <= 30), a t distribution and t value are applied. The CLT does not ap ...
... Z = a value from the normal distribution S = standard error **Note: values for Z vary depending on the probability level. Z = 1.96 (you can use a value of 2 for quick approximations) for 95% confidence limits. For small samples (n <= 30), a t distribution and t value are applied. The CLT does not ap ...
1 - BrainMass
... mean yearly sugar consumption. A sample of 16 people reveals the mean yearly consumption to be 60 pounds with a standard deviation of 20 pounds. 1. What is the value of the population mean? What is the best estimate of this value? 2. Explain why we need to use the t distribution. What assumption do ...
... mean yearly sugar consumption. A sample of 16 people reveals the mean yearly consumption to be 60 pounds with a standard deviation of 20 pounds. 1. What is the value of the population mean? What is the best estimate of this value? 2. Explain why we need to use the t distribution. What assumption do ...
Powerpoint
... are denoted by the Greek letters μ (mu) and (sigma) • They are unknown constants that we would like to estimate • Sample mean and sample standard deviation are denoted by x and s • They are random variables, because their values vary according to the random sample that has been selected ...
... are denoted by the Greek letters μ (mu) and (sigma) • They are unknown constants that we would like to estimate • Sample mean and sample standard deviation are denoted by x and s • They are random variables, because their values vary according to the random sample that has been selected ...
Basic Stats Concepts
... 2) Probability: Statistics is about data while probability is about chance. They are inverses of each other: in descriptive statistics we observe something that did happen. In probability theory we consider some underlying process which has some randomness or uncertainty modeled by random variables, ...
... 2) Probability: Statistics is about data while probability is about chance. They are inverses of each other: in descriptive statistics we observe something that did happen. In probability theory we consider some underlying process which has some randomness or uncertainty modeled by random variables, ...
Review of basic concepts
... Some physical properties are very consistent, that is, they have low variability. An example might be the speed at which steel balls fall in a vacuum - the biggest source of variability is likely to be the accuracy of the timing device. How many sheets of paper do you need to measure to know the ave ...
... Some physical properties are very consistent, that is, they have low variability. An example might be the speed at which steel balls fall in a vacuum - the biggest source of variability is likely to be the accuracy of the timing device. How many sheets of paper do you need to measure to know the ave ...
Study Guide for Exam 3
... • The Binomial Distribution (§7.3) – This is where you do a two-outcome experiment repeatedly and count the number of successes. n = number of times you repeat the experiment p = probability of success during each trial q = 1 − p = probability of failure X = number of successes – Important facts abo ...
... • The Binomial Distribution (§7.3) – This is where you do a two-outcome experiment repeatedly and count the number of successes. n = number of times you repeat the experiment p = probability of success during each trial q = 1 − p = probability of failure X = number of successes – Important facts abo ...
Basic statistics on an array of data points
... Example 1: To find the mean value of the array of data, sum the values of the array and then divide that sum by the number of points n. This follows the definition of the mean of Bevington Eq. 1.1 or Taylor Eq 4.5. ...
... Example 1: To find the mean value of the array of data, sum the values of the array and then divide that sum by the number of points n. This follows the definition of the mean of Bevington Eq. 1.1 or Taylor Eq 4.5. ...
