How do you tell the difference between continuous and discrete data?

How do you tell the difference between continuous and discrete data?

Discrete data is countable while continuous data is measurable. Discrete data contains distinct or separate values. On the other hand, continuous data includes any value within range. Discrete data is graphically represented by bar graph whereas a histogram is used to represent continuous data graphically.

How do you know which measure of central tendency is best?

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.

What is the difference between continuous and discrete model?

Discrete model: the state variables change only at a countable number of points in time. These points in time are the ones at which the event occurs/change in state. Continuous: the state variables change in a continuous way, and not abruptly from one state to another (infinite number of states).

Is age discrete or continuous?

continuous variable
Technically speaking, age is a continuous variable because it can take on any value with any number of decimal places. What is this? If you know someone’s birth date, you can calculate their exact age including years, months, weeks, days, hours, seconds, etc.

Which measure is the most unreliable indicator of central tendency if data are skewed?

So range is obviously going to be the most unreliable indicator of the floor.

What are the factors that you will consider while choosing appropriate measures of central tendency?

It’s important to look the dispersion of a data set when interpreting the measures of central tendency.

• Mean. The mean of a data set is also known as the average value.
• Median. The median of a data set is the value that is at the middle of a data set arranged from smallest to largest.
• Mode.
• Resources.

Which is the most unstable central tendency?

The mean is the most sophisticated of all the measures of central tendency because it incorporates the most information in its calculation, but it is also a relatively “unstable” measure. value of the middle case in a rank-ordered distribution.

What is the most accurate and reliable type to compute for the measures of central tendency and measures of dispersion?

However, in this situation, the mean is widely preferred as the best measure of central tendency because it is the measure that includes all the values in the data set for its calculation, and any change in any of the scores will affect the value of the mean.

Is population discrete or continuous?

Population counts are typically referred to as discrete or quantitative data. Why is population density a continuous data type when it is typically measured for aggregate areas such as census tracts or districts/neighbourhoods (ie, it can’t be measured at any point on a surface like gradient or temperature).

Is temperature continuous or discrete?

Temperature is continuous variable as it does have fractional value too. For example: Today’s temperature is 30. 5 degree Celsius, here 30. 5 is not a discrete variable and hence is a continuous variable.

Is height discrete or continuous?

Height, weight, temperature and length are all examples of continuous data.

Is hours discrete or continuous?

continuous
It depends how did you record the time, e.g. if you count days, or record hours rounded to the nearest hour then it is rather discrete; when you record days, hours and minutes of something happening, then it is closer to continuous.

Which measure of central tendency is not affected by skewed data?

Summary of when to use the mean, median and mode

Type of Variable	Best measure of central tendency
Nominal	Mode
Ordinal	Median
Interval/Ratio (not skewed)	Mean
Interval/Ratio (skewed)	Median

Which measure of central tendency is most appropriate to use when the dataset has an extreme outlier?

The median
What is the most appropriate measure of central tendency when the data has outliers? The median is usually preferred in these situations because the value of the mean can be distorted by the outliers.

What are the three most common measures of central tendency?

There are three main measures of central tendency: the mode, the median and the mean. Each of these measures describes a different indication of the typical or central value in the distribution. What is the mode? The mode is the most commonly occurring value in a distribution.

Which measure of central tendency would be best or most useful measure for each group briefly justify your choice?

What makes a central tendency robust?

The median is a robust measure of central tendency. Taking the same dataset {2,3,5,6,9}, if we add another datapoint with value -1000 or +1000 then the median will change slightly, but it will still be similar to the median of the original data.