Announcement
... Gather measurements on all of the concepts important for your hypothesis (dependent, independent, and control variables). Enter them into a spreadsheet. We will use SPSS in this class. Each row is an observation (unit), each column is a variable. ...
... Gather measurements on all of the concepts important for your hypothesis (dependent, independent, and control variables). Enter them into a spreadsheet. We will use SPSS in this class. Each row is an observation (unit), each column is a variable. ...
Document
... Analysis Requirements What do we look for? In Histograms (one variable): Ideal: Symmetric, bell-shaped. Potential Problems: • Skewness. • Multiple peaks. • Many values at, say, 0, and bell-shaped otherwise. • Outliers. ...
... Analysis Requirements What do we look for? In Histograms (one variable): Ideal: Symmetric, bell-shaped. Potential Problems: • Skewness. • Multiple peaks. • Many values at, say, 0, and bell-shaped otherwise. • Outliers. ...
Slide 1
... The Cartoon Guide to Statistics, Gonick, 1993 An Introduction to Statistical Problem Solving in ...
... The Cartoon Guide to Statistics, Gonick, 1993 An Introduction to Statistical Problem Solving in ...
Chapter 20 - Exploring Marketing Research
... format it is important to have an understanding of the basic tools of data analysis and presentation. What follows is a summary of the basic tools. ...
... format it is important to have an understanding of the basic tools of data analysis and presentation. What follows is a summary of the basic tools. ...
Document
... According to the analysis of a CNN–USA TODAY–Gallup poll conducted in October 2002, “Stress has become a common part of everyday life in the United States. The demands of work, family, and home place an increasing burden on the average American.” According to this poll, 40% of Americans included in ...
... According to the analysis of a CNN–USA TODAY–Gallup poll conducted in October 2002, “Stress has become a common part of everyday life in the United States. The demands of work, family, and home place an increasing burden on the average American.” According to this poll, 40% of Americans included in ...
SAStistics 101
... Not all salaries are equal to the mean, that is, there is variation in salaries. A typical deviation from the mean, above or below, is given by the standard deviation. This corresponds to Std Dev in Figure 1 and is equal to $1,390,922. Note that this value is larger than the mean! When there are se ...
... Not all salaries are equal to the mean, that is, there is variation in salaries. A typical deviation from the mean, above or below, is given by the standard deviation. This corresponds to Std Dev in Figure 1 and is equal to $1,390,922. Note that this value is larger than the mean! When there are se ...
Biostatistics course Part 9 Comparison between two means
... He (she) will apply a Z test to inferences from two independent means. He (she) will apply t test to inferences from a mean of differences in a small sample. He (she) will apply a t test to inferences for two independent means in a small sample. He (she) will obtain a confidence interval for ...
... He (she) will apply a Z test to inferences from two independent means. He (she) will apply t test to inferences from a mean of differences in a small sample. He (she) will apply a t test to inferences for two independent means in a small sample. He (she) will obtain a confidence interval for ...
Lecture 13-14. Sampling.
... The figures below refer to measuring a single key item, while many surveys have multiple items of interest; consequently, the formulas below are not yet an absolute answer, but a guideline to approach more complex statistical issues. Averages. E.g. Average income of US households. X It represents th ...
... The figures below refer to measuring a single key item, while many surveys have multiple items of interest; consequently, the formulas below are not yet an absolute answer, but a guideline to approach more complex statistical issues. Averages. E.g. Average income of US households. X It represents th ...
Random sampling
... – If done with care can give results equivalent to fully random sampling – Caution: if elements in the sampling frame are ordered in a particular way a non-representative sample might be drawn ...
... – If done with care can give results equivalent to fully random sampling – Caution: if elements in the sampling frame are ordered in a particular way a non-representative sample might be drawn ...
Bootstrapping (statistics)
In statistics, bootstrapping can refer to any test or metric that relies on random sampling with replacement. Bootstrapping allows assigning measures of accuracy (defined in terms of bias, variance, confidence intervals, prediction error or some other such measure) to sample estimates. This technique allows estimation of the sampling distribution of almost any statistic using random sampling methods. Generally, it falls in the broader class of resampling methods.Bootstrapping is the practice of estimating properties of an estimator (such as its variance) by measuring those properties when sampling from an approximating distribution. One standard choice for an approximating distribution is the empirical distribution function of the observed data. In the case where a set of observations can be assumed to be from an independent and identically distributed population, this can be implemented by constructing a number of resamples with replacement, of the observed dataset (and of equal size to the observed dataset).It may also be used for constructing hypothesis tests. It is often used as an alternative to statistical inference based on the assumption of a parametric model when that assumption is in doubt, or where parametric inference is impossible or requires complicated formulas for the calculation of standard errors.