PQStat - Baza Wiedzy en:statpqpl

Descriptive analyses

Anonymous (anonymous@undisclosed.example.com) — 2023-03-31T22:15:28+00:00

Descriptive analyses The data collected by the researcher should first be described. Depending on how the measurements are made (on the measurement scale), different measures will be used to describe the variable. Measuring scales The correct determination of the type of analysis to be performed depends on the scale used to represent the collected data. There are 3 main measurement scales:

Diagnostics tests

Anonymous (anonymous@undisclosed.example.com) — 2022-02-13T21:54:04+00:00

Diagnostics tests Evaluation of diagnostic test Suppose that using a diagnostic test we calculate the occurrence of a particular feature (most often disease) and know the gold-standard, so we know that the feature really occurs among the examined people. On the basis of these information, we can build a

Hypothesis testing

Anonymous (anonymous@undisclosed.example.com) — 2022-02-11T12:37:21+00:00

Hypothesis testing he process of generalization of the results obtained from the sample for the whole population is divided into 2 basic parts: * estimation estimating values of the parameters of the population on the basis of the statistical sample,

Hotelling T-square

Anonymous (anonymous@undisclosed.example.com) — 2022-02-13T18:02:06+00:00

Hotelling T-square Analiza Hotellinga zaproponowana została przez Hotellinga (1931) (1947) i Mahalanobisa (1930, 1936) jest rozszerzeniem testów t-Studenta do dziedziny wielu zmiennych. W rezultacie jednoczesnej analizie możemy poddawać wiele różnych cech badanych obiektów.

Installation

Anonymous (anonymous@undisclosed.example.com) — 2022-02-10T21:03:01+00:00

Installation System requirements To use PQStat, your computer must meet the following minimum requirements: * Processor: Intel Pentium II 500MHz * RAM: 512MB * Graphics Card: SVGA 800×600 * Storage: 0.5GB * If using CD version: CD-ROM

Correlation

Anonymous (anonymous@undisclosed.example.com) — 2022-02-13T18:28:03+00:00

Correlation The Correlation coefficients are one of the measures of descriptive statistics which represent the level of correlation (dependence) between 2 or more features (variables). The choice of a particular coefficient depends mainly on the scale, on which the measurements were done. Calculation of coefficients is one of the first steps of the correlation analysis. Then the statistic significance of the gained coefficients may be checked using adequate tests.

With Teacher

Anonymous (anonymous@undisclosed.example.com) — 2023-06-04T16:54:15+00:00

With Teacher The wizard The Wizard is a tool which makes the navigation easier to go, through the basic statistics included in an application, especially for a novice user. It includes suggestions of assumptions which should be checked before the choice of a particular statistic test. The last step of the wizard is to select an appropriate statistic test and to open the

Univariate MANOVA

Anonymous (anonymous@undisclosed.example.com) — 2022-02-13T17:48:27+00:00

Univariate MANOVA The univariate MANOVA Beforehand, we recommend that you read the analysis of T-kwadrat Hotelling'a Multivariate analysis of variance, is an extension of one-way ANOVA for independent groups. It is used to verify the hypothesis that the means of the variables under study are equal across several (

Meta-analysis

Anonymous (anonymous@undisclosed.example.com) — 2022-03-19T11:38:16+00:00

Meta-analysis The number of scientific papers being published has increased tremendously in the last decade. This comes with a number of benefits, but it makes it difficult to keep up with the ever-emerging new information. For example, if a doctor were to use a new treatment for his patients based on a scientific paper he had read, he could make a mistake. The error could come from the fact that a whole host of other papers have been published that contradict th…

Multicomparisons

Anonymous (anonymous@undisclosed.example.com) — 2022-02-13T17:48:17+00:00

Multicomparisons Multicomparisons Simultaneous testing of multiple hypotheses (the so-called family of hypotheses) carries the risk of increasing the error , which is a major problem in the multicomparison field. When the error increases, it means that the null hypothesis is too often rejected when it is true. That is, we too often indicate that there are differences, when in fact there are none. To protect against an increase in

Test power and sample size

Anonymous (anonymous@undisclosed.example.com) — 2022-02-11T09:42:38+00:00

Test power and sample size There are several ways we can approach determining the sample size. One possibility is to estimate how large the sample should be to reflect the population. Another possibility is to estimate the sample size for the situation of applying specific statistical tests. Then, in addition to the necessary sample size, we may be interested in the power of those tests. The first, and seemingly easier approach, is presented in subsection

Normality distribution tests

Anonymous (anonymous@undisclosed.example.com) — 2022-02-09T15:22:07+00:00

Normality distribution tests Testy normalności jednowymiarowej W badaniu normalności rozkładu zastosowanie mogą mieć różne testy, z których każdy zwraca uwagę na nieco inne aspekty rozkładu Gaussa. Nie można wskazać testu dobrego dla każdego możliwego zestawu danych.

Organization of work with the program

Anonymous (anonymous@undisclosed.example.com) — 2022-02-11T10:46:17+00:00

Organization of work with the program All statistical analysis procedures are available in the Statistics menu. Forma organizacji danych Forma organizacji danych zależy od procedur statystycznych, jakie użytkownik planuje wykonać. Analiza statystyczna danych może dotyczyć danych zebranych w postaci tabeli kontyngencji lub danych w postaci surowej. Przy czym istnieje możliwość zamiany danych:

Plots

Anonymous (anonymous@undisclosed.example.com) — 2022-02-09T14:50:06+00:00

Plots Program PQStat oferuje wykresy kolumnowe, wykresy błędów, wykresy typu ramka-wąsy, punktowe, liniowo-punktowe. Okno z ustawieniami opcji wykresów wywołujemy poprzez menu Wykresy. Zmiana podstawowych parametrów wykresu jest możliwa bezpośrednio w oknie wykresu. Jeśli natomiast:

Comparison - one group

Anonymous (anonymous@undisclosed.example.com) — 2022-02-12T16:15:38+00:00

Comparison - one group Parametric tests The t-test for a single sample The single-sample test is used to verify the hypothesis, that an analysed sample with the mean () comes from a population, where mean () is a given value. Basic assumptions:

Comparison - two groups

Anonymous (anonymous@undisclosed.example.com) — 2022-02-12T16:16:25+00:00

Comparison - two groups Parametric tests The Fisher-Snedecor test The F-Snedecor test is based on a variable which was formulated by Fisher (1924), and its distribution was described by Snedecor. This test is used to verify the hypothesis about equality of variances of an analysed variable for 2 populations.

Comparison - more than two groups

Anonymous (anonymous@undisclosed.example.com) — 2022-02-12T16:23:01+00:00

Comparison - more than two groups Note The proposed test selection scheme for the multiple group comparison is not the only possible scheme and does not include all the tests proposed in the software for this comparison. Note Note, that simultaneous comparison of more than two groups can NOT be replaced with multiple performance the

Dimension reduction and grouping

Anonymous (anonymous@undisclosed.example.com) — 2022-02-16T09:09:17+00:00

Dimension reduction and grouping As the number of variables subjected to a statistical analysis grows, their precision grows, but so does the level of complexity and difficulty in interpreting the obtained results. Too many variables increase the risk of their mutual correlation. The information carried by some variables can, then, be redundant, i.e. a part of the variables may not bring in new information for analysis but repeat the information already given by other variables. The need for di…

Probability distributions

Anonymous (anonymous@undisclosed.example.com) — 2022-02-11T12:22:12+00:00

Probability distributions A real data distribution from a sample - empirical data distribution may be carried out in a mean of a ''frequency tables'' (by selecting Statistic menu→Descriptive analysis)→Frequency tables). For example, a distribution of the amount of used free minutes by subscribers of some mobile network operator

Reliability analysis

Anonymous (anonymous@undisclosed.example.com) — 2022-02-16T10:41:44+00:00

Reliability analysis Reliability analysis is usually associated with the complex scale construction, in particular summary scales (these consist of many individual items). Reliability analysis, associated as its internal consistency, informs us to what extent a particular scale measures what it should measure. In other words, to what extend the scale items measure the things that are measured by the whole scale

en:statpqpl:statpl

Anonymous (anonymous@undisclosed.example.com) — 2014-08-09T16:22:59+00:00

Spis treści PQStat - Baza Wiedzy index

Survival analysis

Anonymous (anonymous@undisclosed.example.com) — 2022-02-16T09:35:42+00:00

Survival analysis Survival analysis is often used in medicine. In other fields of study it is also called reliability analysis, duration analysis, or event history analysis. Its main goal is to evaluate the remaining time of the survival of, for example, patients after an operation. Its main purpose is to evaluate the survival time of e.g. patients after surgery - the tools used here are life tables and Kaplan-Meier curves. Another interesting aspect is the comparison of survival times e.g. sur…

Program operation

Anonymous (anonymous@undisclosed.example.com) — 2022-02-09T20:13:30+00:00

Program operation Documents management is based on projects. Each project is a separate file. A project is similar to a worksheet. It consists of 3 basic elements elementy: * Datasheets (including map sheets and matrixs) - the number of sheets in a given project is limited to 1000,

Analysis for stratas

Anonymous (anonymous@undisclosed.example.com) — 2022-02-13T18:02:16+00:00

Analysis for stratas The Mantel-Haenszel method for several tables The Mantel-Haenszel method for tables proposed by Mantel and Haenszel (1959) then it was extended by Mantel (1963). A wider review the development of these methods was carried out i.a. by Newman (2001)

Multidimensional models

Anonymous (anonymous@undisclosed.example.com) — 2023-03-31T19:20:50+00:00

Multidimensional models Multivariate regression models provide an opportunity to study the effects of multiple independent variables (multiple factors) and their interactions on a single dependent variable. Through multivariate models, it is also possible to build many simplified models at the same time - one-dimensional (univariate) models. The information about which model we want to build (

Agreement analysis

Anonymous (anonymous@undisclosed.example.com) — 2022-02-13T20:56:36+00:00

Agreement analysis Parametric tests The Intraclass Correlation Coefficient and a test to examine its significance The intraclass correlation coefficient is used when the measurement of variables is done by a few „raters” (). It measures the strength of