**the mean**, the median, and the mode. The mean is the sum of the values, divided by the number of values.

What is measure of straight angle?

**what is the measure of right angle and straight angle**.

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Measures of location describe the central tendency of the data. They include the mean, median and mode. Mean or Average. The (arithmetic) mean, or average, of n observations (pronounced “x bar”) is simply **the sum of the observations divided by the number of observations**; thus: ˉx=SumofallsamplevaluesSamplesize=∑xin.

A fundamental task in many statistical analyses is **to estimate a location parameter for the distribution**; i.e., to find a typical or central value that best describes the data. The mean is that value that is most commonly referred to as the average.

The median is **the middle value in the sense that half the data are above it**, and half the data are below it. If there are an odd number of data points, the median is the middle value, e.g., 5 for data set A.

A measure of central location is the single value that best represents a characteristic such as age or height of a group of persons. A measure of dispersion **quantifies how much persons in the group vary from each other** and from our measure of central location.

In descriptive statistics we use location **measures in order to describe the central value or central position of a distribution**. Among the most important are: arithmetic mean. median. mode.

What are measures of variation? Measures of variation describe **the width of a distribution**. They define how spread out the values are in a dataset. They are also referred to as measures of dispersion/spread.

Levels of measurement | Examples | Measure of central tendency |
---|---|---|

Nominal | Ethnicity Political ideology | Mode |

Ordinal | Level of anxiety Income bracket | Mode Median |

Interval and ratio | Reaction time Test score Temperature | Mode Median Mean |

A distribution is characterized by three values: Location. **The location is the expected value of the output being measured**. For a stable process, this is the value around which the process has stabilized.

**The mean** is the most frequently used measure of central tendency because it uses all values in the data set to give you an average. For data from skewed distributions, the median is better than the mean because it isn’t influenced by extremely large values.

A measure of dispersion indicates **the scattering of data**. … In other words, dispersion is the extent to which values in a distribution differ from the average of the distribution. It gives us an idea about the extent to which individual items vary from one another, and from the central value.

When you have a symmetrical distribution for continuous data, the **mean, median**, and mode are equal. In this case, analysts tend to use the mean because it includes all of the data in the calculations. However, if you have a skewed distribution, the median is often the best measure of central tendency.

The common measures of location are **quartiles** and percentiles. Quartiles are special percentiles. … The median, M, is called both the second quartile and the 50th percentile.

**Standard error and standard deviation** are both measures of variability. The standard deviation reflects variability within a sample, while the standard error estimates the variability across samples of a population.

Recall that a measure of center, or central tendency, is a single number used to describe a set of numeric data. It describes a typical value within the data set. … A measure of variability is a single number used to describe the **spread** of a data set.

Statistics have majorly categorised into two types: **Descriptive statistics**. **Inferential statistics**.

Measures of central tendency are called such **because they tell us what is happening in the middle of the data**.

**Mean** is generally considered the best measure of central tendency and the most frequently used one. However, there are some situations where the other measures of central tendency are preferred. There are few extreme scores in the distribution.

The four measures of central tendency are **mean, median, mode and the midrange**. Here, mid-range or mid-extreme of a set of statistical data values is the arithmetic mean of the maximum and minimum values in a data set.

**The median** is usually preferred to other measures of central tendency when your data set is skewed (i.e., forms a skewed distribution) or you are dealing with ordinal data. However, the mode can also be appropriate in these situations, but is not as commonly used as the median.

Numerical MeasureSensitive MeasureResistant MeasureMeasure of CenterMeanMedianMeasure of Spread (Variation)Standard Deviation (SD)Interquartile Range (IQR)

The standard deviation is **a measure of spread**. We use it as a measure of spread when we use the mean as a measure of center.

If the distribution is not symmetric, then it is skewed. Most frequently occurring observation of a variable. A variable may have no **mode** or more than one mode. The mode is the only meaningful measure of central location for a categorical variable.

Dispersion refers to **the range of potential outcomes of investments based on historical volatility or returns**. Dispersion can be measured using alpha and beta, which measure risk-adjusted returns and returns relative to a benchmark index, respectively.

**Standard deviation (SD)** is the most commonly used measure of dispersion. It is a measure of spread of data about the mean. SD is the square root of sum of squared deviation from the mean divided by the number of observations.

The Quartile Deviation (QD) is **the product of half of the difference between the upper and**. **lower quartiles**. Mathematically we can define as: Quartile Deviation = (Q3 – Q1) / 2. Quartile Deviation defines the absolute measure of dispersion.

The median is **the middle number in a sorted, ascending or descending, list of numbers** and can be more descriptive of that data set than the average. … If there is an even amount of numbers in the list, the middle pair must be determined, added together, and divided by two to find the median value.

Why is it important to consider all the measures of location in reporting statistics? **Each of the measures has advantages and disadvantages in representing the data**. Why would one use a grouped mean or standard deviation?

Mean, median and modal value belong to the **location parameter** (Measurement of Central Tendency) in descriptive statistics. They are also called measures of central tendency.

75th Percentile – Also known as the **third**, or upper, quartile. The 75th percentile is the value at which 25% of the answers lie above that value and 75% of the answers lie below that value.

The most common measures of position are **percentiles, quartiles, and standard scores** (aka, z-scores).

D5 = Value of 5 (30 + 1) / 10. D5 = Value of **15.5th** position, halfway between scores 76 and 78. 50% of the scores fall below 77.

Variability, almost by definition, is **the extent to which data points in a statistical distribution or data set diverge**—vary—from the average value, as well as the extent to which these data points differ from each other.

Variability refers to **how spread scores are in a distribution out**; that is, it refers to the amount of spread of the scores around the mean. For example, distributions with the same mean can have different amounts of variability or dispersion.