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Q 1
Q 1

... displaying, summarizing, and asking questions about data. Definitions: Individuals – objects (people, animals, things) described by a set of data ...
Glossary
Glossary

... An approach to measurement in which you obtain data from individuals representing all segments of a population. CONTRAST WITH longitudinal. cross tabulation A procedure by which you make a two-dimensional table with rows corresponding to the values of one variable and columns corresponding to the va ...
Calculating R 2
Calculating R 2

... calculate a p-value (what is this??) • Old school: one can consult a t-table where the degrees of freedom (the number of observations - 1) and your level of security (p<.10, .05 or .01 for ex.) decides whether your coefficient is significantly different from zero or not (t-table – can be found as ap ...
collection/analysis slides
collection/analysis slides

... We did not detect a difference, but could still be different Did not find a counter-example to null hypothesis Provides evidence for Lifelines = PerspWall, but not proof Boring! Basically found nothing ...
Statistics and Research
Statistics and Research

... We need a clear and objective way to compare differences and possible outcomes ...
File - TAU R Workshop 2015
File - TAU R Workshop 2015

... We can see here that our models: 24 months, 9271 ₪ and 173 cm are not very successful The Residual Is how much a certain value is far from the prediction of the model . Omri Caspi is far away in 32 cm from the model “Israeli = 173” and in 29 cm from the more complicated model: “Israeli man = 177, Is ...
Data Analysis in Business Research
Data Analysis in Business Research

... values below the mean are distributed exactly as the values above the mean. In this case, the low and high values balance each other out. In a skewed distribution, the values are not symmetrical around the mean. This results in an imbalance of low or high values. Skewness is a measure of asymmetry i ...
Let`s explore SAS Proc T-Test
Let`s explore SAS Proc T-Test

... probability of observing a greater absolute value of t under the null hypothesis. For a onetailed test, halve this probability. If p-value is less than the pre-specified alpha level (usually .05 or .01) we will conclude that mean is statistically significantly different from zero. In our example, th ...
CHAPTER 8
CHAPTER 8

... The regression-discontinuity design is used in cases where it would not be practical to have another group exposed to the treatment or to serve as a control group. The design indicates differences that occur at the point of treatment which would differentiate post-treatment scores of those having be ...
ppt - UAH Department of Electrical and Computer Engineering
ppt - UAH Department of Electrical and Computer Engineering

... How many measurements are required to get a desired level of statistical confidence? How to summarize the results of several different workloads on a single computer system? How to compare two or more computer systems using several different workloads? Is comparing the mean sufficient? What model be ...
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... My experience of teaching and lecturing Mathematics and Statistics for more than 15 years from secondary school up to university level, it has become evident that statistical courses have always been taught in isolation of real life and practical problems. In this regard, many pupils, students and t ...
New tools and graphical aids for Business Mathematics 1
New tools and graphical aids for Business Mathematics 1

... multiplication and 1 division). This number decreases if any of the values are identical to the mean. In addition, this method also requires counting the number of values which are larger than the mean and the number of the values which are smaller than the mean. This can be considered as easier and ...
Quiz 1 12pm Class Question: What determines which numerical
Quiz 1 12pm Class Question: What determines which numerical

... will you use in each case? Here are your answers in random order. See my comments. it must include a graphical display. A histogram would be a good method to give an appropriate description of a quantitative value. This does not answer the question. For the quantative variable, the "average" must ma ...
File - Mr. Campbell
File - Mr. Campbell

... where, how, and by whom were the data produced? The two major types of variables studied in this unit are categorical and quantitative variables. A categorical variable (qualitative data) places an individual into one of several groups or categories. These values fall into separate, nonoverlapping c ...
Statistics 1 Revision Notes
Statistics 1 Revision Notes

... Example: When a die is rolled, we say that the probability of each number is . This is a statistical model, but the assumption that each face is equally likely might not be true. Suppose the die is weighted to increase the chance of a six. We might then find, after experimenting, that the probabilit ...
Multiple Regression - Kean University: Office of Research and
Multiple Regression - Kean University: Office of Research and

... inflates the standard errors. Thus, it makes some variables statistically insignificant while they should be otherwise significant. Unusual and Influential data A single observation that is substantially different from all other observations can make a large difference in the results of your regres ...
Introduction - University of Toronto
Introduction - University of Toronto

... • SRS helps eliminate the problem of having the sample reflect a different population than the one we are interested in studying. ...
Measures of central tendency: The mean
Measures of central tendency: The mean

... small.[7] Therefore, it is not an appropriate measure of central tendency for skewed distribution.[8] ...
Descriptive Statistics - CSUSB Math Department
Descriptive Statistics - CSUSB Math Department

... !  Find the mean !  Find the deviation of each value from the mean !  Square the deviations !  Sum the squared deviations !  Divide the sum by n-1 (for samples only) ...
Analyzing Data
Analyzing Data

... • ONLY when presented with categorical data (which in AP Bio is almost NEVER) • Examples of categorical data  size of a population by age range  Number of deaths by causes of death  Size of different populations in an ...
This page
This page

... that lists all the ages in years of the respondents to our survey. One of the variables (d1_age) in our data set does this. But we could also divide age into a series of categories such as under 30, 30 to 39, 40 to 49, 50 to 59, 60 to 69, and 70 and older. In a grouped frequency distribution the mod ...
descriptive statistics and exploratory data analysis
descriptive statistics and exploratory data analysis

... also shows the normal curve superimposed over the histogram. It also allows to examine various aspects of the distribution qualitatively. For example, the distribution could be bimodal (have 2 peaks). This might suggest that the sample is not homogeneous but possibly its elements came from two diffe ...
week2
week2

... • A large number or numerical methods are available for describing quantitative data sets. Most of these methods measure one of two data characteristics:  The central tendency of the set of observations – it is the tendency of the data to cluster, or center, about certain numerical values. ...
Testing Non-Inferiority with Two Independent Samples
Testing Non-Inferiority with Two Independent Samples

... This option specifies whether higher values are better (e.g. points in a game of football) or worse (e.g. points in a game of golf). This option defines whether higher values of the response variable are to be considered better or worse. This choice determines the direction of the non-inferiority te ...
Unit 1.2 Lecture Notes COMPLETE
Unit 1.2 Lecture Notes COMPLETE

... There is a major assumption being made when using the 68-95 Rule and that is that the data is normally distributed. We will talk more about this idea in Unit 1.3 but for now, know that this means the distribution is spread about the mean proportionally to it’s standard deviation. In otherwords N(x,s ...
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Categorical variable

In statistics, a categorical variable is a variable that can take on one of a limited, and usually fixed, number of possible values, thus assigning each individual to a particular group or ""category."" In computer science and some branches of mathematics, categorical variables are referred to as enumerations or enumerated types. Commonly (though not in this article), each of the possible values of a categorical variable is referred to as a level. The probability distribution associated with a random categorical variable is called a categorical distribution.Categorical data is the statistical data type consisting of categorical variables or of data that has been converted into that form, for example as grouped data. More specifically, categorical data may derive from either or both of observations made of qualitative data, where the observations are summarised as counts or cross tabulations, or of quantitative data, where observations might be directly observed counts of events happening or might be counts of values that occur within given intervals. Often, purely categorical data are summarised in the form of a contingency table. However, particularly when considering data analysis, it is common to use the term ""categorical data"" to apply to data sets that, while containing some categorical variables, may also contain non-categorical variables.A categorical variable that can take on exactly two values is termed a binary variable or dichotomous variable; an important special case is the Bernoulli variable. Categorical variables with more than two possible values are called polytomous variables; variables are often assumed to be polytomous unless otherwise specified. Discretization is treating continuous data as if it were categorical. Dichotomization is treating continuous data or polytomous variables as if they were binary variables. Regression analysis often treats category membership as a quantitative dummy variable.
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