# observedmoments

From betafunctions v1.4.0
by Haakon Haakstad

##### Compute Moments of Observed Value Distribution.

Computes Raw, Central, or Standardized moment properties of a vector of observed scores.

##### Usage

```
observedmoments(
x,
type = c("raw", "central", "standardized"),
orders = 4,
correct = TRUE
)
```

##### Arguments

- x
A vector of values, the distribution of which moments are to be calculated.

- type
A character vector determining which moment-types are to be calculated. Permissible values are

`"raw"`

,`"central"`

, and`"standardized"`

.- orders
The number of moment-orders to be calculated for each of the moment-types.

- correct
Logical. Whether to include bias correction in estimation of orders. Default is

`TRUE`

.

##### Value

A list of moment types, each a list of moment orders.

##### Examples

```
# NOT RUN {
# Generate some fictional data. Say, 100 individuals take a test with a
# maximum score of 100 and a minimum score of 0.
set.seed(1234)
testdata <- rbinom(100, 100, rBeta.4P(100, .25, .75, 5, 3))
hist(testdata, xlim = c(0, 100))
# To compute the first four raw, central, and standardized moments for this
# distribution of observed scores using observedmoments():
observedmoments(x = testdata, type = c("raw", "central", "standardized"),
orders = 4, correct = TRUE)
# }
```

*Documentation reproduced from package betafunctions, version 1.4.0, License: CC0*

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