Definition of StatisticComplete sufficient statisticIs “test statistic” a value or a random variable?Example of sample $X_1,X_2,ldots,X_n$Expected value of iid random variablesAnalytical properties of sample quantiles in statistical packages“Let random variables $X_1,dots, X_n$ be a iid random sample from $f(x)$” - what does it mean?Is $barX_n = dfrac(X_1 + X_2 + … + X_n)n$ an estimator of the mean in general (for random variables with any distribution)?What is statistic in statistics?Statistics can't be a function of a parameter - but isn't the sample a function of the parameter?Sufficient statistics - how can the con. pdf not depend on θ when θ is in the equation?
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Definition of Statistic
Complete sufficient statisticIs “test statistic” a value or a random variable?Example of sample $X_1,X_2,ldots,X_n$Expected value of iid random variablesAnalytical properties of sample quantiles in statistical packages“Let random variables $X_1,dots, X_n$ be a iid random sample from $f(x)$” - what does it mean?Is $barX_n = dfrac(X_1 + X_2 + … + X_n)n$ an estimator of the mean in general (for random variables with any distribution)?What is statistic in statistics?Statistics can't be a function of a parameter - but isn't the sample a function of the parameter?Sufficient statistics - how can the con. pdf not depend on θ when θ is in the equation?
$begingroup$
I keep seeing conflicting definitions of a statistic. Is a statistic a random variable such that it is a function of the random variables of a random sample? Or is it the value of the function of the random sample, after each random variable of the random sample has taken on a specific value?
$$(1) S=f(X_1,X_2...X_n)$$
$$(2) s=f(x_1,x_2...x_n)$$
I haven't been able to get any clarification for this and I've seen the term statistic describe both situations
estimation sampling inference random-variable interpretation
New contributor
$endgroup$
add a comment |
$begingroup$
I keep seeing conflicting definitions of a statistic. Is a statistic a random variable such that it is a function of the random variables of a random sample? Or is it the value of the function of the random sample, after each random variable of the random sample has taken on a specific value?
$$(1) S=f(X_1,X_2...X_n)$$
$$(2) s=f(x_1,x_2...x_n)$$
I haven't been able to get any clarification for this and I've seen the term statistic describe both situations
estimation sampling inference random-variable interpretation
New contributor
$endgroup$
$begingroup$
It seems that there are also plenty of conflicting views on estimator and estimate which go hand in hand with this. As an estimator is supposed to be a kind of statistic, whether an estimator is a random variable or not would also clarify some things. There seems to be a lot of conflicting definitions on this site though.
$endgroup$
– Colin Hicks
6 hours ago
add a comment |
$begingroup$
I keep seeing conflicting definitions of a statistic. Is a statistic a random variable such that it is a function of the random variables of a random sample? Or is it the value of the function of the random sample, after each random variable of the random sample has taken on a specific value?
$$(1) S=f(X_1,X_2...X_n)$$
$$(2) s=f(x_1,x_2...x_n)$$
I haven't been able to get any clarification for this and I've seen the term statistic describe both situations
estimation sampling inference random-variable interpretation
New contributor
$endgroup$
I keep seeing conflicting definitions of a statistic. Is a statistic a random variable such that it is a function of the random variables of a random sample? Or is it the value of the function of the random sample, after each random variable of the random sample has taken on a specific value?
$$(1) S=f(X_1,X_2...X_n)$$
$$(2) s=f(x_1,x_2...x_n)$$
I haven't been able to get any clarification for this and I've seen the term statistic describe both situations
estimation sampling inference random-variable interpretation
estimation sampling inference random-variable interpretation
New contributor
New contributor
New contributor
asked 6 hours ago
Colin HicksColin Hicks
1183
1183
New contributor
New contributor
$begingroup$
It seems that there are also plenty of conflicting views on estimator and estimate which go hand in hand with this. As an estimator is supposed to be a kind of statistic, whether an estimator is a random variable or not would also clarify some things. There seems to be a lot of conflicting definitions on this site though.
$endgroup$
– Colin Hicks
6 hours ago
add a comment |
$begingroup$
It seems that there are also plenty of conflicting views on estimator and estimate which go hand in hand with this. As an estimator is supposed to be a kind of statistic, whether an estimator is a random variable or not would also clarify some things. There seems to be a lot of conflicting definitions on this site though.
$endgroup$
– Colin Hicks
6 hours ago
$begingroup$
It seems that there are also plenty of conflicting views on estimator and estimate which go hand in hand with this. As an estimator is supposed to be a kind of statistic, whether an estimator is a random variable or not would also clarify some things. There seems to be a lot of conflicting definitions on this site though.
$endgroup$
– Colin Hicks
6 hours ago
$begingroup$
It seems that there are also plenty of conflicting views on estimator and estimate which go hand in hand with this. As an estimator is supposed to be a kind of statistic, whether an estimator is a random variable or not would also clarify some things. There seems to be a lot of conflicting definitions on this site though.
$endgroup$
– Colin Hicks
6 hours ago
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
A statistic is a function that maps from the set of outcomes of the observable values to a real number. Thus, with $n$ data points, a statistic will be a function $s: mathbbR^nrightarrow mathbbR$ as in your second form. However, it is also possible to view the statistic in its random sense by taking the appropriate composition of function with the original random variables. (Remember that each random variable $X_i: Omega rightarrow mathbbR$ is a measurable function that maps from the sample space to the real numbers.) That is, you can form the random variable $S: Omega rightarrow mathbbR$ as:
$$S(omega) = s(X_1(omega), ..., X_n(omega)).$$
The random variable $S$ is the random version of the statistic $s$. Both are often referred to as "statistics", but it is important to bear in mind that $S$ is a composition with the functions for the observable random variables.
$endgroup$
$begingroup$
that was very helpful. A lot of this notation is really confusing and seems at time almost conflicting as in this case where the term can be used in both contexts.
$endgroup$
– Colin Hicks
6 hours ago
add a comment |
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$begingroup$
A statistic is a function that maps from the set of outcomes of the observable values to a real number. Thus, with $n$ data points, a statistic will be a function $s: mathbbR^nrightarrow mathbbR$ as in your second form. However, it is also possible to view the statistic in its random sense by taking the appropriate composition of function with the original random variables. (Remember that each random variable $X_i: Omega rightarrow mathbbR$ is a measurable function that maps from the sample space to the real numbers.) That is, you can form the random variable $S: Omega rightarrow mathbbR$ as:
$$S(omega) = s(X_1(omega), ..., X_n(omega)).$$
The random variable $S$ is the random version of the statistic $s$. Both are often referred to as "statistics", but it is important to bear in mind that $S$ is a composition with the functions for the observable random variables.
$endgroup$
$begingroup$
that was very helpful. A lot of this notation is really confusing and seems at time almost conflicting as in this case where the term can be used in both contexts.
$endgroup$
– Colin Hicks
6 hours ago
add a comment |
$begingroup$
A statistic is a function that maps from the set of outcomes of the observable values to a real number. Thus, with $n$ data points, a statistic will be a function $s: mathbbR^nrightarrow mathbbR$ as in your second form. However, it is also possible to view the statistic in its random sense by taking the appropriate composition of function with the original random variables. (Remember that each random variable $X_i: Omega rightarrow mathbbR$ is a measurable function that maps from the sample space to the real numbers.) That is, you can form the random variable $S: Omega rightarrow mathbbR$ as:
$$S(omega) = s(X_1(omega), ..., X_n(omega)).$$
The random variable $S$ is the random version of the statistic $s$. Both are often referred to as "statistics", but it is important to bear in mind that $S$ is a composition with the functions for the observable random variables.
$endgroup$
$begingroup$
that was very helpful. A lot of this notation is really confusing and seems at time almost conflicting as in this case where the term can be used in both contexts.
$endgroup$
– Colin Hicks
6 hours ago
add a comment |
$begingroup$
A statistic is a function that maps from the set of outcomes of the observable values to a real number. Thus, with $n$ data points, a statistic will be a function $s: mathbbR^nrightarrow mathbbR$ as in your second form. However, it is also possible to view the statistic in its random sense by taking the appropriate composition of function with the original random variables. (Remember that each random variable $X_i: Omega rightarrow mathbbR$ is a measurable function that maps from the sample space to the real numbers.) That is, you can form the random variable $S: Omega rightarrow mathbbR$ as:
$$S(omega) = s(X_1(omega), ..., X_n(omega)).$$
The random variable $S$ is the random version of the statistic $s$. Both are often referred to as "statistics", but it is important to bear in mind that $S$ is a composition with the functions for the observable random variables.
$endgroup$
A statistic is a function that maps from the set of outcomes of the observable values to a real number. Thus, with $n$ data points, a statistic will be a function $s: mathbbR^nrightarrow mathbbR$ as in your second form. However, it is also possible to view the statistic in its random sense by taking the appropriate composition of function with the original random variables. (Remember that each random variable $X_i: Omega rightarrow mathbbR$ is a measurable function that maps from the sample space to the real numbers.) That is, you can form the random variable $S: Omega rightarrow mathbbR$ as:
$$S(omega) = s(X_1(omega), ..., X_n(omega)).$$
The random variable $S$ is the random version of the statistic $s$. Both are often referred to as "statistics", but it is important to bear in mind that $S$ is a composition with the functions for the observable random variables.
answered 6 hours ago
BenBen
26.5k229124
26.5k229124
$begingroup$
that was very helpful. A lot of this notation is really confusing and seems at time almost conflicting as in this case where the term can be used in both contexts.
$endgroup$
– Colin Hicks
6 hours ago
add a comment |
$begingroup$
that was very helpful. A lot of this notation is really confusing and seems at time almost conflicting as in this case where the term can be used in both contexts.
$endgroup$
– Colin Hicks
6 hours ago
$begingroup$
that was very helpful. A lot of this notation is really confusing and seems at time almost conflicting as in this case where the term can be used in both contexts.
$endgroup$
– Colin Hicks
6 hours ago
$begingroup$
that was very helpful. A lot of this notation is really confusing and seems at time almost conflicting as in this case where the term can be used in both contexts.
$endgroup$
– Colin Hicks
6 hours ago
add a comment |
Colin Hicks is a new contributor. Be nice, and check out our Code of Conduct.
Colin Hicks is a new contributor. Be nice, and check out our Code of Conduct.
Colin Hicks is a new contributor. Be nice, and check out our Code of Conduct.
Colin Hicks is a new contributor. Be nice, and check out our Code of Conduct.
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$begingroup$
It seems that there are also plenty of conflicting views on estimator and estimate which go hand in hand with this. As an estimator is supposed to be a kind of statistic, whether an estimator is a random variable or not would also clarify some things. There seems to be a lot of conflicting definitions on this site though.
$endgroup$
– Colin Hicks
6 hours ago