A powerful test is the chi-square contingency table.
Yes they are.
Any kind of data - nominal, ordinal or interval - provided you can group the data into a few categories. Ideally not more than seven, though in exceptional cases, up to ten may be used.
There are a number of appropriate displays to show the measures of variation for a data set. Different graphs can be used for this purpose which may include histograms, stemplots, dotplots and boxplots among others.
ANOVA is a statistical test of whether the means of several groups are all equal. The chi-square test of association is used to test the null hypothesis that there is no association between two nominal scale variables. It does not require a distinction between independent and dependent variables.
The mode can be used with both kinds of data. The median may be used with ordinal data but great care is required if the median falls between two classes of observations.The mode can be used with both kinds of data. The median may be used with ordinal data but great care is required if the median falls between two classes of observations.The mode can be used with both kinds of data. The median may be used with ordinal data but great care is required if the median falls between two classes of observations.The mode can be used with both kinds of data. The median may be used with ordinal data but great care is required if the median falls between two classes of observations.
No, it is not suitable for nominal data.
Bar charts are used to summarise nominal or ordinal data.
Yes they are.
Date of birth is not considered nominal data; it is typically classified as ordinal or continuous data. While it consists of categories (days, months, years), it also has a meaningful order and can be used to calculate age. This allows for comparisons and statistical analyses that are not possible with purely nominal data, which lacks a natural ordering.
Nominal data is characterized as data that is used to define a group of category. Some examples include color of eyes, and color of hair.
ANOVA (Analysis of Variance) is used for interval and ratio level data because it relies on the assumption that the data is continuous and normally distributed, allowing for meaningful calculations of means and variances. Nominal and ordinal data do not meet these criteria; nominal data consists of categorical variables without a numerical relationship, while ordinal data has a ranked order but does not provide equal intervals between ranks. Consequently, ANOVA is not appropriate for these data types as it cannot accurately assess differences in means or variances.
Chi-square is a statistic used to assess the degree of the relationship and degree of association between two nominal variables
Any kind of data - nominal, ordinal or interval - provided you can group the data into a few categories. Ideally not more than seven, though in exceptional cases, up to ten may be used.
Nominal numbers are numbers used for identification only. They do not indicate quantity, rank, or any other measurement. The properties of nominal numbers are the minimum required to refer to an entity as a number. The term "nominal number" is quite recent, and appears to have originated as a usage in school textbooks derived from the statistical term "nominal data", defined as data indicating "...merely statements of qualitative category of membership." Mathematicians would typically describe this concept simply as a mapping between objects, or sets of objects, to the ordinal numbers.
measures used to protect the computer from making saved data be erased.
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The answer depends on the type of distribution for the data. It could be the modal class.