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Catégorie :Category: nCreator TI-Nspire
Auteur Author: nesero
Type : Classeur 3.0.1
Page(s) : 1
Taille Size: 3.73 Ko KB
Mis en ligne Uploaded: 23/10/2024 - 19:54:28
Uploadeur Uploader: nesero (Profil)
Téléchargements Downloads: 1
Visibilité Visibility: Archive publique
Shortlink : http://ti-pla.net/a4271420
Type : Classeur 3.0.1
Page(s) : 1
Taille Size: 3.73 Ko KB
Mis en ligne Uploaded: 23/10/2024 - 19:54:28
Uploadeur Uploader: nesero (Profil)
Téléchargements Downloads: 1
Visibilité Visibility: Archive publique
Shortlink : http://ti-pla.net/a4271420
Description
Fichier Nspire généré sur TI-Planet.org.
Compatible OS 3.0 et ultérieurs.
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DEFINITIONS A variable is a characteristic, number or quantity that can be measured (or counted). Each of this measurements is called a data point. We can measure several variables at the same time. In this case we say that out data is multidimensional. We can write our data as a table. Each column correspond to one variable, and each line correspond to a simultanous measurement (a record, or by extension, a data point). Such a table, is a very simple example of database, which is a organized collection of data and information. VISUALIZING VARIABLE DATA | Type of Data | Pie Chart | Line Chart | Bar Chart | Histogram | Scatter Plot (2 variables or more) | | Categorical | X | | X | | | | Ordinal | X | X | | | | | Discrete | | X | X | X | | | Continu (1 var) | | X | | X | | | Continuo(2 var) | | X | | | X | Note: This table provides suggestions for the type of graphs that are usually more useful for a given type of data. However, the choice of chart will always depend on the context and the specific questions we ask of the data MEASURES OF LOCATION DEFINITIONS " Arithmetic mean (also called average): Sum of all numbers divided by size of dataset. Applies only to numeric data (discrete or continuous) " Median: Middle value when data arranged in order Applies to ordinal and numeric data " Mode: Most frequently occurring value Can be used with qualitative data, and numeric, but for continuous data, it must be applied to the distribution (or frequency table) mean= (20 x 1 + 30 x 2 + 50 x 3 + 25 x 4 + 5 x 5 )/N = Sum (Freq x X)/N = 355/130 = 2,73 DEFINITIONS Variance: Variance is a statistical measurement that describes the spread or dispersion of a set of data points around the mean (average). It calculates how far each data point is from the mean, and then averages these squared differences. Variance helps to understand the degree of variability in the dataset. Standard Deviation: Standard deviation is the square root of the variance. It provides a measure of dispersion in the same units as the original data, making it easier to interpret compared to variance. It reflects how much the individual data points deviate, on average, from the mean. Range: The range is the simplest measure of dispersion. It is the difference between the maximum and minimum values in a dataset. The range gives a quick sense of how spread out the data are but doesn't provide information about how the data is distributed between those values. Coefficient of Variation (CV): The coefficient of variation is a relative measure of dispersion that expresses the standard deviation as a percentage of the mean. It is used to compare the degree of variation between datasets with different units or different scales. A higher CV indicates greater variability relative to the mean. CORRELATION Correlation is a measure of association of two variables. There are several definitions for correlation. The most important are: Pearson (or linear) correlation (numeric data only) Spearman (or rank) correlation (numeric and ordinal data) If we have a data set with more than two variables, we compute the correlation for each pair of variables. We speak about the correlation between two variables. That is, correlation between X and Y is the same as correlation between Y and X. It is a symmetric quantity. INDEPENDENCY " Two variables are independent if knowing the value of one of them, give some indication about the value of the second. " If two variables are independent, then the correlation must be zero " The converse is NOT true Made with nCreator - tiplanet.org
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Compatible OS 3.0 et ultérieurs.
<<
DEFINITIONS A variable is a characteristic, number or quantity that can be measured (or counted). Each of this measurements is called a data point. We can measure several variables at the same time. In this case we say that out data is multidimensional. We can write our data as a table. Each column correspond to one variable, and each line correspond to a simultanous measurement (a record, or by extension, a data point). Such a table, is a very simple example of database, which is a organized collection of data and information. VISUALIZING VARIABLE DATA | Type of Data | Pie Chart | Line Chart | Bar Chart | Histogram | Scatter Plot (2 variables or more) | | Categorical | X | | X | | | | Ordinal | X | X | | | | | Discrete | | X | X | X | | | Continu (1 var) | | X | | X | | | Continuo(2 var) | | X | | | X | Note: This table provides suggestions for the type of graphs that are usually more useful for a given type of data. However, the choice of chart will always depend on the context and the specific questions we ask of the data MEASURES OF LOCATION DEFINITIONS " Arithmetic mean (also called average): Sum of all numbers divided by size of dataset. Applies only to numeric data (discrete or continuous) " Median: Middle value when data arranged in order Applies to ordinal and numeric data " Mode: Most frequently occurring value Can be used with qualitative data, and numeric, but for continuous data, it must be applied to the distribution (or frequency table) mean= (20 x 1 + 30 x 2 + 50 x 3 + 25 x 4 + 5 x 5 )/N = Sum (Freq x X)/N = 355/130 = 2,73 DEFINITIONS Variance: Variance is a statistical measurement that describes the spread or dispersion of a set of data points around the mean (average). It calculates how far each data point is from the mean, and then averages these squared differences. Variance helps to understand the degree of variability in the dataset. Standard Deviation: Standard deviation is the square root of the variance. It provides a measure of dispersion in the same units as the original data, making it easier to interpret compared to variance. It reflects how much the individual data points deviate, on average, from the mean. Range: The range is the simplest measure of dispersion. It is the difference between the maximum and minimum values in a dataset. The range gives a quick sense of how spread out the data are but doesn't provide information about how the data is distributed between those values. Coefficient of Variation (CV): The coefficient of variation is a relative measure of dispersion that expresses the standard deviation as a percentage of the mean. It is used to compare the degree of variation between datasets with different units or different scales. A higher CV indicates greater variability relative to the mean. CORRELATION Correlation is a measure of association of two variables. There are several definitions for correlation. The most important are: Pearson (or linear) correlation (numeric data only) Spearman (or rank) correlation (numeric and ordinal data) If we have a data set with more than two variables, we compute the correlation for each pair of variables. We speak about the correlation between two variables. That is, correlation between X and Y is the same as correlation between Y and X. It is a symmetric quantity. INDEPENDENCY " Two variables are independent if knowing the value of one of them, give some indication about the value of the second. " If two variables are independent, then the correlation must be zero " The converse is NOT true Made with nCreator - tiplanet.org
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