# Statistic

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A. The ordinal level of measurement is most appropriate because the data can be ordered but differences obtained by subtraction cannot be found or are meaningless.
Determine which of the four levels of measurement​ (nominal, ordinal,​ interval, ratio) is most appropriate for the data below. ratings of novels
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The ordinal level of measurement is most appropriate because categories are ordered but differences cannot be found or are meaningless.
Determine which of the four levels of measurement​ (nominal, ordinal,​ interval, ratio) is most appropriate. Ranks of cars evaluated by a consumer's magazine. .
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nominal level of measurement is most appropriate because the data cannot be ordered
Determine which of the four levels of measurement​ (nominal, ordinal,​ interval, ratio) is most appropriate for the data below. Companies that produced movies in 2007
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The ratiolevel of measurement is most appropriate because the data can can be ordered , differences obtained by subtraction and there is a natural starting zerozero point.
Determine which of the four levels of measurement​ (nominal, ordinal,​ interval, ratio) is most appropriate for the data below.
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Such data are not counts or measures of​ anything, so it makes no sense to compute their average​ (mean).
identify the level of measurement of the​ data, and explain what is wrong with the given calculation. In a​ survey, the hair color of respondents are identified as 10 for brown hair , 20for blond hair , 30 for black hair , and 40 for anything else. The average​ (mean) is calculated for 714 respondents and the result is 22.3 .
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A parameter is a numerical measurement of a​ population; a statistic is a numerical measurement of a sample.
How do a parameter and a statistic​ differ?
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The value is a statistic because it is a numerical measurement describing some characteristic of a sample.
Determine whether the given value is a statistic or a parameter.A survey found that 83% of all respondents were optimistic.
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statistic because the value is a numerical measurement describing a characteristic of a sample