Bao Wen Chen (beconomist)'s Public Profile in the Diigo Community

More »

Tags

Recent Tags:	Statistics(0), MIT(0), Programming(0), Python(0), Internet(0), software(0), Taiwan(0), Energy(0), Computer Science(0), Algorithm(0), Taipei(0), WebTech(0), Transportation Research & Policy(0), New York(0), OpenGovernance(0), Facebook(0), Europe(0), Google(0), Innovation(0)
Top Tags:	WebTech(118), Mathematics(95), Statistics(57), Economics & Behavioral Economics(50), Journals(47), 東京大学(46), Taiwan(39), GIS(33), OpenSource(32), Social(32)

More »

Recent Bookmarks and Annotations

Confidence interval - Wikipedia, the free encyclopedia about 10 hours ago
- In statistics, a confidence interval (CI) is a particular kind of interval estimate of a population parameter. Instead of estimating the parameter by a single value, an interval likely to include the parameter is given. Thus, confidence intervals are used to indicate the reliability of an estimate. How likely the interval is to contain the parameter is determined by the confidence level or confidence coefficient. Increasing the desired confidence level will widen the confidence interval.
- The calculation of a confidence interval generally requires assumptions about the nature of the estimation process – it is primarily a parametric method – for example, it may depend on an assumption that the distribution of the population from which the sample came is normal. As such, confidence intervals as discussed below are not robust statistics, though modifications can be made to add robustness – see robust confidence intervals.
- 1 more annotations...
- - Confidence intervals are used within Neyman–Pearson (frequentist) statistics
Non-parametric statistics - Wikipedia, the free encyclopedia about 10 hours ago
- In statistics, the term non-parametric statistics covers a range of topics:
  
  distribution free methods which do not rely on assumptions that the data are drawn from a given probability distribution. As such it is the opposite of parametric statistics. It includes non-parametric statistical models, inference and statistical tests.
  non-parametric statistic can refer to a statistic (a function on a sample) whose interpretation does not depend on the population fitting any parametrized distributions. Statistics cased on the ranks of observations are one example of such statistics and these play a central role in many non-parametric approaches.
  non-parametric regression refers to modelling where the structure of the relationship between variables is treated non-parametrically, but where nevertheless there may be parametric assumptions about the distribution of model residuals.
- Non-parametric models differ from parametric models in that the model structure is not specified a priori but is instead determined from data. The term nonparametric is not meant to imply that such models completely lack parameters but that the number and nature of the parameters are flexible and not fixed in advance.
Normalization (statistics) - Wikipedia, the free encyclopedia about 11 hours ago
- In one usage in statistics, normalization is the process of removing statistical error in repeated measured data.
- this allows data on different scales to be compared, by bringing them to a common scale. In terms of levels of measurement, these ratios only make sense for ratio measurements (where ratios of measurements are meaningful), not interval measurements (where only distances are meaningful, but not ratios).
- 4 more annotations...
- - Standard score
    $\frac{X - \mu}{\sigma}$
    Normalizing errors when population parameters are known.
  - Student's t-statistic
    $\frac{X - \overline{X}}{s}$
    Normalizing residuals when population parameters are unknown (estimated).
  - Standardized moment
    $\frac{\mu_k}{\sigma^k}$
    Normalizing moments, using the standard deviation $σ$ as a measure of scale.
  - Coefficient of variation
    $\frac{\sigma}{\mu}$
    Normalizing dispersion, using the mean $μ$ as a measure of scale, particularly for positive distribution such as the exponential distribution and Poisson distribution.
Standard score - Wikipedia, the free encyclopedia on 2009-11-23
- In statistics, a standard score indicates how many standard deviations an observation or datum is above or below the mean. It is a dimensionless quantity derived by subtracting the population mean from an individual raw score and then dividing the difference by the population standard deviation.
- The standard deviation is the unit of measurement of the z-score. It allows comparison of observations from different normal distributions, which is done frequently in research.
- 4 more annotations...
- - The z-score is only defined if one knows the population parameters, as in standardized testing; if one only has a sample set, then the analogous computation with sample mean and sample standard deviation yields the Student's t-statistic.
  - A key point is that calculating z requires the population mean and the population standard deviation, not the sample mean or sample deviation. It requires knowing the population parameters, not the statistics of a sample drawn from the population of interest. But knowing the true standard deviation of a population is often unrealistic except in cases such as standardized testing, where the entire population is measured.
  - The z-score is most often used in the z-test in standardized testing – the analog of the Student's t-test for a population whose parameters are known, rather than estimated. As it is very unusual to know the entire population, the t-test is much more widely used.
  - In mathematical statistics, a random variable X is standardized using the theoretical (population) mean and standard deviation:
    
    $Z = {X - \mu \over \sigma}$
    
    where μ = E(X) is the mean and σ = the standard deviation of the probability distribution of X.
    
    If the random variable under consideration is the sample mean:
    
    $\bar{X}={1 \over n} \sum_{i=1}^n X_i$
    
    then the standardized version is
    
    $Z={\bar{X}-\mu\over\sigma/\sqrt{n}}.$
    
    See normalization (statistics) for other forms of normalization.
Student's t-statistic - Wikipedia, the free encyclopedia on 2009-11-23
- a t-statistic is, broadly speaking, a statistic whose sampling distribution is a Student's t-distribution. These are a parametric statistic, most frequently used in statistical hypothesis testing in Student's t-tests, but can be defined and used independently of hypothesis testing.
Distribution Function -- from Wolfram MathWorld on 2009-11-23
- The distribution function , also called
  the cumulative distribution function (CDF) or cumulative frequency function, describes
  the probability that a variate takes on a value less than or equal to a number
  .
- The distribution function is therefore related to a continuous probability density function by
  
  (1)
  
  (2)
  
  so (when it exists) is simply the derivative
  of the distribution function
  
  (3)
  
  Similarly, the distribution function is related to a discrete probability by
  
  (4)
Standard Normal Distribution -- from Wolfram MathWorld on 2009-11-23
- A standard normal distribution is a normal distribution with zero mean () and unit variance (), given
  by the probability density
  function and distribution
  function
  
  (1)
  
  (2)
  
  over the domain .
  
  It has mean, variance, skewness,
  and kurtosis excess given by
  
  (3)
  
  (4)
  
  (5)
Marketing research - Wikipedia, the free encyclopedia on 2009-11-23
- Marketing research is often partitioned into two sets of categorical pairs, either by target market:
  
  Consumer marketing research, and
  Business-to-business (B2B) marketing research
  Qualitative marketing research, and
  Quantitative marketing research
- The goal of marketing research is to identify and assess how changing elements of the marketing mix impacts customer behavior.
- 1 more annotations...
- - Marketing managers make numerous strategic and tactical decisions in the process of identifying and satisfying customer needs. They make decisions about potential opportunities, target market selection, market segmentation, planning and implementing marketing programs, marketing performance, and control. These decisions are complicated by interactions between the controllable marketing variables of product, pricing, promotion, and distribution. Further complications are added by uncontrollable environmental factors such as general economic conditions, technology, public policies and laws, political environment, competition, and social and cultural changes.
Likert scale - Wikipedia, the free encyclopedia on 2009-11-23
- it is better, therefore, to reserve the term Likert scale to apply to the summated scale, and Likert item to refer to an individual item.
- Likert scaling is a bipolar scaling method, measuring either positive or negative response to a statement. Sometimes a four-point scale is used; this is a forced choice method^{[citation needed]} since the middle option of "Neither agree nor disagree" is not available.
- 3 more annotations...
- - Respondents may avoid using extreme response categories (central tendency bias); agree with statements as presented (acquiescence bias); or try to portray themselves or their organization in a more favorable light (social desirability bias). Designing a scale with balanced keying (an equal number of positive and negative statements) can obviate the problem of acquiescence bias, since acquiescence on positively keyed items will balance acquiescence on negatively keyed items, but central tendency and social desirability are somewhat more problematic.
  - Whether individual Likert items can be considered as interval-level data, or whether they should be considered merely ordered-categorical data is the subject of disagreement. Many regard such items only as ordinal data, because, especially when using only five levels, one cannot assume that respondents perceive all pairs of adjacent levels as equidistant. On the other hand, often (as in the example above) the wording of response levels clearly implies a symmetry of response levels about a middle category; at the very least, such an item would fall between ordinal- and interval-level measurement; to treat it as merely ordinal would lose information. Further, if the item is accompanied by a visual analog scale, where equal spacing of response levels is clearly indicated, the argument for treating it as interval-level data is even stronger.
  - When treated as ordinal data, Likert responses can be collated into bar charts, central tendency summarised by the median or the mode (but some would say not the mean), dispersion summarised by the range across quartiles (but some would say not the standard deviation), or analyzed using non-parametric tests, e.g. chi-square test, Mann–Whitney test, Wilcoxon signed-rank test, or Kruskal–Wallis test.^[4] Parametric analysis of ordinary averages of Likert scale data is also justifiable by the Central Limit Theorem, although some would disagree that ordinary averages should be used for Likert scale data.
    
    Responses to several Likert questions may be summed, providing that all questions use the same Likert scale and that the scale is a defendable approximation to an interval scale, in which case they may be treated as interval data measuring a latent variable. If the summed responses fulfill these assumptions, parametric statistical tests such as the analysis of variance can be applied. These can be applied only when the more than 5 Likert questions are summed.
Ogive - Wikipedia, the free encyclopedia on 2009-11-22
- In statistics, an ogive is a graph showing the curve of a cumulative distribution function^[3

More »

Bookmark Lists

R Language

More »

Groups

Ubuntu - Linux for human beings

48 members, 78 items

Ubuntu is a the MOST Popular Linux Operating System (OS). More Fast,Secure,Robust then Window$ or Mac. Here u will find Ubuntu Related Tutorials, News,Tips,Tricks, also Linux Humor & Parody Too :)) http://ubuntu.com

Bao Wen Chen's Profile

More »

Tags

More »

Recent Bookmarks and Annotations

More »

Bookmark Lists

More »

Groups

Ubuntu - Linux for human beings

Bao Wen Chen follows 1 people

Recent Visitors (22 visits)

Me elsewhere

			(1)
			(2)

			(4)

			(1)
			(2)

			(3)
			(4)
			(5)

Bao Wen Chen's Profile

More » Tags

More » Recent Bookmarks and Annotations

More » Bookmark Lists

More » Groups

Ubuntu - Linux for human beings

Bao Wen Chen follows 1 people

Recent Visitors (22 visits)

Me elsewhere

More »

Tags

More »

Recent Bookmarks and Annotations

More »

Bookmark Lists

More »

Groups