The mean of grouped data
is preferred because it is more accurate as compared to the mean of ungrouped data. The mean of ungrouped data may lead to wrong manipulation of the median therefore it is considered inefficient in most cases.
Why is it usually better to calculate a mode from grouped rather than ungrouped data?
Answer: becaz sometimes we could not able to find mode in grouped data or we get more than one mode in grouped data. but in ungrouped their is a specific formula for ungrouped data and we can able to find a perfect answer.so,
calculating mode in ungrouped is better
than grouped data.
When it is more convenient to use grouped data?
It is convenient to use grouped data
than single data as it gives more accuracy to the required result
.
How do you know if data is grouped or ungrouped?
When the data has not been placed in any categories and no aggregation/summarization has taken placed on the data
then it is known as ungrouped data. Ungrouped data is also known as raw data. What is grouped data? When raw data have been grouped in different classes then it is said to be grouped data.
What are the disadvantages of using a grouped data over a ungrouped data?
3.It is compute the given data for obtaining the result Disadvantages : 1.It is not well defined. 2.
It is not based on all the values.
3.It is stable for large values and it will not be well defined if the data consists of small number of values. 4.It is not capable of further mathematical treatment.
Can mode be calculated for grouped data?
Yes, we can calculate the mode for a group of data with
unequal class interval or class size
. … The class which has the maximum height will be the required modal class, containing the mode. Hence, we can say that the mode can be calculated for grouped data with unequal Class interval or class sizes.
What is the formula of mode for grouped data?
Mode for grouped data is given as
Mode=l+(f1−f02f1−f0−f2)×h
, where l is the lower limit of modal class, h is the size of class interval, f1 is the frequency of the modal class, f0 is the frequency of the class preceding the modal class, and f2 is the frequency of the class succeeding the modal class.
Why is grouped data more accurate?
When calculating the means of grouped and ungrouped data, there will be a variation. The
mean of grouped data is preferred because it is more accurate as compared to the mean of ungrouped data
. The mean of ungrouped data may lead to wrong manipulation of the median therefore it is considered inefficient in most cases.
Which of the following is are important when getting the mean of a grouped data?
To calculate the mean of grouped data, the first step is to
determine the midpoint (also called a class mark) of each interval, or class
. These midpoints must then be multiplied by the frequencies of the corresponding classes. The sum of the products divided by the total number of values will be the value of the mean.
What is grouped and ungrouped data?
What is grouped data and ungrouped data? Grouped data means
the data (or information) given in the form of class intervals
such as 0-20, 20-40 and so on. Ungrouped data is defined as the data given as individual points (i.e. values or numbers) such as 15, 63, 34, 20, 25, and so on.
How can we convert ungrouped data into grouped data?
How can we convert ungrouped data to grouped data? The first step is to
determine how many classes you want to have
. Next, you subtract the lowest value in the data set from the highest value in the data set and then you divide by the number of classes that you want to have.
Does ungrouped data frequency?
Ungrouped data is data
given as indi- vidual
data
points.
Grouped data is data
given in intervals. Example 3.
Ungrouped data
without a
frequency
distribution.
Is grouped data quantitative or qualitative?
Quantitative data
is also known as numerical data while qualitative data is also known as categorical data. This is because quantitative data are measured in the form of numbers or counts. for qualitative data, they are grouped into categories.
What are the disadvantages of using grouped data?
Grouping does lose precision and any graphs, tables
, or statistics generated from grouped data will not be as exact as if raw data would be used. With computers, grouped data should not be used for computing statistics. The primary use for grouped data is for making graphs or tables.
What are the advantages of using grouped data?
The advantages of grouping data are, it
improves the accuracy/ efficiency of estimation, helps to focus on the important subpopulations
, and ignores irrelevant ones.
Is primary data and ungrouped data are same?
The information was collected by the investigator (student ) with a definite objective , the data obtained is called primary data. Ungrouped data is
raw data
. The data has not been sorted into any groups or categories.
