Transformation Normal Distribution Questions and Answers
Voting Question: is this algebra 1 or 2 stuff? and whats the difference between advanced algebra 2 and advanced algebra 2 Honrs?
* Chapter 1: Tools of Algebra o Lesson 1: Properties of Real Numbers o Lesson 2: Algebraic Expressions o Lesson 3: Solving Equations o Lesson 4: Solving Inequalities o Lesson 5: Absolute Value Equations and Inequalities o Lesson 6: Probability * Chapter 2: Functions, Equations, and Graphs o Lesson 1: Relations and Functions o Lesson 2: Linear Equations o Lesson 3: Direct Variation o Lesson 4: Using Linear Models o Lesson 5: Absolute Value Functions and Graphs o Lesson 6: Families of Functions o Lesson 7: Two-Variable Inequalities * Chapter 3: Linear Systems o Lesson 1: Graphing Systems of Equations o Lesson 2: Solving Systems Algebraically o Lesson 3: Systems of Inequalities o Lesson 4: Linear Programming o Lesson 5: Graphs in Three Dimensions o Lesson 6: Systems with Three Variables * Chapter 4: Matrices o Lesson 1: Organizing Data into Matrices o Lesson 2: Adding and Subtracting Matrices o Lesson 3: Matrix Multiplication o Lesson 4: Geometric Transformations with Matrices o Lesson 5: 2 × 2 Matrices, Determinants, and Inverses o Lesson 6: 3 × 3 Matrices, Determinants, and Inverses o Lesson 7: Inverse Matrices and Systems o Lesson 8: Augmented Matrices and Systems * Chapter 5: Quadratic Equations and Functions o Lesson 1: Modeling Data with Quadratic Functions o Lesson 2: Properties of Parabolas o Lesson 3: Transforming Parabolas o Lesson 4: Factoring Quadratic Expressions o Lesson 5: Quadratic Equations o Lesson 6: Complex Numbers o Lesson 7: Completing the Square o Lesson 8: The Quadratic Formula * Chapter 6: Polynomials and Polynomial Functions o Lesson 1: Polynomial Functions o Lesson 2: Polynomials and Linear Factors o Lesson 3: Dividing Polynomials o Lesson 4: Solving Polynomial Equations o Lesson 5: Theorems about Roots of Polynomial Equations o Lesson 6: The Fundamental Theorem of Algebra o Lesson 7: Permutations and Combinations o Lesson 8: The Binomial Theorem * Chapter 7: Radical Functions and Rational Exponents o Lesson 1: Roots and Radical Expressions o Lesson 2: Multiplying and Dividing Radical Expressions o Lesson 3: Binomial Radical Expressions o Lesson 4: Rational Exponents o Lesson 5: Solving Square Root and Other Radical Equations o Lesson 6: Function Operations o Lesson 7: Inverse Relations and Functions o Lesson 8: Graphing Square Root and Other Radical Functions * Chapter 8: Exponential and Logarithmic Functions o Lesson 1: Exploring Exponential Models o Lesson 2: Properties of Exponential Functions o Lesson 3: Logarithmic Functions as Inverses o Lesson 4: Properties of Logarithms o Lesson 5: Exponential and Logarithmic Equations o Lesson 6: Natural Logarithms * Chapter 9: Rational Functions o Lesson 1: Inverse Variation o Lesson 2: The Reciprocal Function Family o Lesson 3: Rational Functions and their Graphs o Lesson 4: Rational Expressions o Lesson 5: Adding and Subtracting Rational Expressions o Lesson 6: Solving Rational Equations o Lesson 7: Probability of Multiple Events * Chapter 10: Quadratic Relations and Conic Sections o Lesson 1: Exploring Conic Sections o Lesson 2: Parabolas o Lesson 3: Circles o Lesson 4: Ellipses o Lesson 5: Hyperbolas o Lesson 6: Translating Conic Sections * Chapter 11: Sequences and Series o Lesson 1: Mathematical Patterns o Lesson 2: Arithmetic Sequences o Lesson 3: Geometric Sequences o Lesson 4: Arithmetic Series o Lesson 5: Geometric Series o Lesson 6: Area Under a Curve * Chapter 12: Probability and Statistics o Lesson 1: Probability Distributions o Lesson 2: Conditional Probability o Lesson 3: Analyzing Data o Lesson 4: Standard Deviation o Lesson 5: Working With Samples o Lesson 6: Binomial Distributions o Lesson 7: Normal Distributions * Chapter 13: Periodic Functions and Trigonometry o Lesson 1: Exploring Periodic Data o Lesson 2: Angles and the Unit Circle o Lesson 3: Radian Measure o Lesson 4: The Sine Function o Lesson 5: The Cosine Function o Lesson 6: The Tangent Function o Lesso moreResolved Question: Transforming data to normal distribution?
Is it acceptable to just square all the data in order to try to make the data closer to a normal distribution? Is this an acceptable transformation? I've tried the arc-sine, square root, and reciprocal transformations and none of these work for my data. Thanks moreResolved Question: Can someone check my work?
Can someone check this for me? 1. The two branches of statistical methods are a. theoretical and inferential. b. intuitive and observational. c. descriptive and intuitive. *d. descriptive and inferential. 2. Which of the following was a behavioral psychologist who was opposed to the use of statistics in psychology? a. Cohen. b. McCracken. c. Cronbach. *d. Skinner. 3. Sixty years ago, opinion polls often used the _(*quota sampling*) method of sampling, which is now largely discredited. 4. How do you set up a hypothesis testing problem? a. You set it up to test what you predict will happen. *b. You set it up to test the opposite of what you predict will happen. c. You set up two problems, one to test what you predict and the other to test the opposite. d. You set up a test that assumes the two populations are different, regardless of whether that is what you predict or not. 5. As the number of people in each sample gets larger, the distribution of means a. begins to look less and less like the normal curve. *b. becomes a better approximation of the normal curve. c. becomes more positively skewed. d. becomes more negatively skewed. 6. In studies using a very large number of participants, it is common to get statistically significant results that have a very small _(*p value*)________. 7. If a sample has 27 people in it, the degrees of freedom used in the formula to estimate the population variance would be *a. 26 b. 27 c. 272 d. 27 8. All of the following are true for both the t test for independent means AND the t test for dependent means, EXCEPT a. population variances are estimated from the information in the sample of scores actually studied. b. pretest-posttest experimental designs are common. c. the population means are unknown. *d. the sample scores (in some form) are eventually compared to a t distribution. 9. To test the null hypothesis that three populations have equal means, you carry out a(n) (*between-groups estimate of the population variance.*) 10. A consumer psychologist is interested in the effects of Annual Income and Motivations to Shop on shopping patterns of consumers. Annual Income (broken into two levels: High and Moderate) and Motivation to Shop (with three levels: Escape, Necessity, and Socializing) are considered in one study. How many cells will there be? a. 2. *b. 3. c. 4. d. 6. 11. The dots on a scatter diagram seem to form a straight line that goes upward to the right. This situation is called *a. a positive linear correlation. b. a negative linear correlation. c. a curvilinear correlation. d. no correlation. 12. You want to predict college grades from high school grades. College grades are the a. predictor variable. *b. criterion variable. c. independent variable. d. causal variable. 13. A contingency table is a table in which *a. the distributions of two nominal variables are laid out so that you have the frequencies of their combinations as well as the totals. b. chi-squares for each category are displayed over each level of the predictor variable. c. F distributions are translated into t distributions. d. ï£2 distributions are translated into F distributions. 14. In a square-root transformation, a. high numbers become lower, and low numbers become higher. b. moderate numbers remain unchanged, but low numbers become slightly higher. c. low numbers become much lower, but high numbers remain basically unchanged. *d. moderate numbers become only slightly lower, but high numbers become much lower. 15. A problem with using _(*test re-test*) reliability for a test of knowledge (such as a vocabulary test) is that when people take it the second time, their performance is likely to be different as a result of having taken the test once My answers have a * by it... the ones that have the (*....*) in it mean that it was a fill in the blank and the words in the () are my answer moreResolved Question: Can someone check this for me?
1.The two branches of statistical methods are a.theoretical and inferential. b.intuitive and observational. c.descriptive and intuitive. *d.descriptive and inferential. 2.Which of the following was a behavioral psychologist who was opposed to the use of statistics in psychology? a.Cohen. b.McCracken. c.Cronbach. *d.Skinner. 3.Sixty years ago, opinion polls often used the _(*quota sampling*) method of sampling, which is now largely discredited. 4.How do you set up a hypothesis testing problem? a.You set it up to test what you predict will happen. *b.You set it up to test the opposite of what you predict will happen. c.You set up two problems, one to test what you predict and the other to test the opposite. d.You set up a test that assumes the two populations are different, regardless of whether that is what you predict or not. 5.As the number of people in each sample gets larger, the distribution of means a.begins to look less and less like the normal curve. *b.becomes a better approximation of the normal curve. c.becomes more positively skewed. d.becomes more negatively skewed. 6.In studies using a very large number of participants, it is common to get statistically significant results that have a very small _(*p value*)________. 7.If a sample has 27 people in it, the degrees of freedom used in the formula to estimate the population variance would be *a. 26 b. 27 c. 272 d.27 8.All of the following are true for both the t test for independent means AND the t test for dependent means, EXCEPT a.population variances are estimated from the information in the sample of scores actually studied. b.pretest-posttest experimental designs are common. c.the population means are unknown. *d.the sample scores (in some form) are eventually compared to a t distribution. 9.To test the null hypothesis that three populations have equal means, you carry out a(n) (*between-groups estimate of the population variance.*) 10.A consumer psychologist is interested in the effects of Annual Income and Motivations to Shop on shopping patterns of consumers. Annual Income (broken into two levels: High and Moderate) and Motivation to Shop (with three levels: Escape, Necessity, and Socializing) are considered in one study. How many cells will there be? a.2. *b.3. c.4. d.6. 11.The dots on a scatter diagram seem to form a straight line that goes upward to the right. This situation is called *a.a positive linear correlation. b.a negative linear correlation. c.a curvilinear correlation. d.no correlation. 12.You want to predict college grades from high school grades. College grades are the a.predictor variable. *b.criterion variable. c.independent variable. d.causal variable. 13.A contingency table is a table in which *a.the distributions of two nominal variables are laid out so that you have the frequencies of their combinations as well as the totals. b.chi-squares for each category are displayed over each level of the predictor variable. c.F distributions are translated into t distributions. d.ï£2 distributions are translated into F distributions. 14.In a square-root transformation, a.high numbers become lower, and low numbers become higher. b.moderate numbers remain unchanged, but low numbers become slightly higher. c.low numbers become much lower, but high numbers remain basically unchanged. *d.moderate numbers become only slightly lower, but high numbers become much lower. 15.A problem with using _(*test re-test*) reliability for a test of knowledge (such as a vocabulary test) is that when people take it the second time, their performance is likely to be different as a result of having taken the test once all the answers that I answered have a * by them... Can someone please tell me if I got any wrong and what umber it is that I got wrong. Thanks so much moreResolved Question: Question regarding Variance in a normal distribution as a transformation of 2 random variables?
X and Y are independent random variables with mean 6 and 7, and standard deviation 1 and 3/4 respectively. W = X - Y. I understand that the mean of W is -1, but I'm not sure why the variance of W is 25/16. I know that the variance of X is 1 and variance of Y is 9/16, and that adding them you get 25/16, I'm curious why the variance of W is the sum of the individual variances, rather than the difference. Could someone explain this to me? I really appreciate the help! moreResolved Question: Normal Distribution Transformations?
If, X~N(1,1) and Y~N(0,2), how do you find the transformation of 2X + 2Y. I know the answer will be 2X+2Y ~N(2,12) but im not sure how to get about it, is there a set answer to get there? yeah but the answer in the book is as above. is there any formula on the internet which this method is proven? or shown with other examples? moreResolved Question: Statistics Question: What transformation do I use for my data?
My data set has a huge number of zeros and as such I have a J shaped distribution curve. How can I transform my data so I have a normal distribution? moreResolved Question: Mathematical Statistics - Normal Distribution?
Given a random variable X such that X is N(1,4), what is P(1<x^2<9)? This seems easy, but I'm having trouble getting the answer in the back of the book: 0.477. How do you deal with the x-squared? I know if you substitute for V=((x-mu)/sigma)^2, then V has a Chi^2(1) distribution, but I can't figure out how to do that here. Also, when I try to use a simple transformation like Y=X^2, that doesn't seem to work either. Thanks! moreResolved Question: exploratory data analysis and transformations?
Hi, I'm working on a data set where the outcome is a proportion. The majority of my observations are 0%, and hence I need to use a transformation. My question is, should I carry out my exploratory analysis (i.e. scatterplots or whatever) on the RAW data or on the TRANSFORMED data? or do you only need to use a transformation when you are using more complex methods such as regression analysis which assumes the normal distribution? Thanks, Nicola umm....P.W. I seriously hope you're not a statistician. Non-normal data needs to be transformed prior to most classical statistical methods because the methods assume a normal distribution. haha, well I'm not a statistician either...hence the question. moreResolved Question: (x,y) manipulation for normal distribution curve
If X is a normally distributed random variable with µ = 5 and sdev = 3, then the transformation that maps the curve of the density function of X, f(x), to the curve of the standard normal distribution is what? Is it (x, y) ---> ( 3(x - 5), y/3 ) Thanks! moreResolved Question: Normal distribution to standardized normal distribution?
what steps are involved in transforming the normal distribution to the standardized normal distribution? what is the advantage of this transformation? moreResolved Question: Statistical validity of comparing transformed and non-transformed data with parametric tests.?
Two different algorithms solve the same problem 30 times each, producing two sets of 30 results (60 results in total). I want to determine if the null hypothesis is correct (that both algorithms perform equally well), hopefully using a parametric test (unpaired t-test). Assumptions for t-test include equal variances between the two groups, and that the data results from a normal distribution. Applying the Anderson-Darling test for normality invalidates the normality assumption for a single group, but not the other. I still have to implement the Levene test to check on variances, so for the moment I can't comment on the other assumption. My question is simple: Is it statistically valid to transform the one non-normal group using a Box-Cox transformation and then performing the relevant t-test? (either normal t-test, or Welch t-test if variances differ). As a sub-question, how do you go about reporting your analysis in a paper (do you mention transformation, box-cox coefficient etc)? moreResolved Question: transformation?
let X1 and X2 be 2 independent standard normal random variable. Let Y= (X1-X2)^2/2. Find the distribution of Y. moreTransformation Normal Distribution News
transformation normal distribution
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Controul > Random numbers: standard normal distribution in flash/as3
An implementation of the Marsaglia polar transform in Actionscript (a method for generation of standard normal random numbers from uniformly distributed random input) built into a Park-Miller pseudo-random number generator. moreAyaanBayaan (AB) News - One designer blouse for many sarees ...
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If we know that X is normally distributed, how would we show that cX+d is normally distributed, for c and d real numbers? In particular if X is a standard distribution (ie with mean 0 and variance 1)? moreFormation of Microstructures and Continuous Heating and Time ...
Formation of Microstructures and Continuous Heating and Time–Temperature Transformation Diagrams of YBa. 2. Cu. 3. O. 7Àx. Film. Fabricated by Metal Organic Deposition with Trifluoroacetates. Nobuyuki M ..... The initial distribution of the above particles is given as the log-normal distribution. ÁX Â ÁX (mm. 2. ) elements for finite difference method (FDM) are selected (numbers: n x and n y. ) to simulate the Y123-crystal growth. The growth rates V c of c-plane (c- ... moreSome notes on cinemetrics
Usually, such a transformation involves using logarithms. Once the data has been transformed to its logarithm, we can then run tests to see if the data now follows a normal distribution: if it does, then we say that the data is ... moreGetting data ready for a transformation or distribution fitting ...
In Lean Six Sigma projects and many data analysis efforts you need to describe the data with a distribution or to transform it to a normal distribution to assist in the analysis. A quick answer is to adjust the data so that it is skewed ... moreMy Experimentation on ..: Is e Normal?
The final step in producing the table of "random digits" was to transform the table by adding pairs of digits modulo 10. This was done "in order to improve the distribution of the digits". There were 20000 punched cards with 50 digits ... moreMarlborough Localvore: FMNZ Update and Chairpersons report 2009
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What's most intriguing about this "normal" distribution is that it is not normal at all. As I said, the test questions are tweaked in such a way so that a bell curve is created. It's like carving a duck from a piece of wood: you carve ... moreApplication of Excel function tutorials: Statistical functions (b)
Purposes: to return to point x of the Fisher transform. Generate a transformation similar to the normal distribution rather than a function of skew, use this function to complete the assumption that the correlation coefficient test. ... moreWarning: file(http://beta.search.msn.com/results.aspx?q=transformation+normal+distribution&format=rss&FORM=R0RE) [function.file]: failed to open stream: HTTP request failed! HTTP/1.0 400 Bad Request in /home/yourwe24/public_html/normal/gaat/soeke.php on line 4
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