Factors We Consider When Determining Frequency Distribution
Students and researchers may require help to determine frequency distribution, especially when handling descriptive and predictive analytics. In our service, we provide a complete list of scores or values in a particular variable and the number of times they appear in a dataset.
The frequency distribution can be presented in a graphical or tabular format. Our experts are always ready and capable of preparing a graphical representation or a tabular format of frequency distribution depending on what the client prefers.
Frequency distribution tables and graphs are mostly used to organize data and provide an overview of the distribution of numeric and categorical variables in a given dataset.
Whether the client needs us to make a frequency distribution table or a graphical representation of values, we ensure that the number of scores occurring in the dataset is correctly described and all relevant calculations conducted accordingly.
This article contains a detailed description of the factors considered in the frequency distribution conducted by our experts on a particular data set to display the pattern and the number of observations for a specific variable.
Conducting frequency distribution is dependent on various factors including the nature of the provided data and the objects of classification preferred by the client. In our help to conduct frequency distribution, we assist the clients in viewing scores and their corresponding number of occurrences within a full range of observations in an organized manner.
The frequency distribution can demonstrate either the actual number of observations that fall in each range or the percentage frequency of such observations. Discussed below are some of the factors we consider when conducting frequency distribution.
1. The type of variables/data on which to conduct frequency distributions
When given a dataset to conduct frequency distribution, it is our responsibility to first perform explanatory data analysis (EDA) to gain an understanding of the data type and the nature of variables.
There are rules that apply to continuous data only while others are observed with discrete data that only contains numeric variables. Likewise, in a frequency distribution, some rules are applicable only with continuous variables as others are used on categorical variables. It is after classifying the data and the variables contained in a given dataset that a decision on the type of frequency distribution to conduct can be made.
2. The type of frequency distribution
There are various types of frequency distributions that we consider in descriptive statistics to help one have a clear view of how observations are distributed on a measurement scale. These include:
- Grouped frequency distribution.
- Ungrouped frequency distribution.
- Cumulative frequency distribution.
- Relative frequency distribution.
Those who purchase the services of a statistician from our company receive customized assistance depending on the nature of their data and the type of variables in the dataset. We carefully select the type of frequency distribution that aligns with the client's needs.
3. Objects of classification
When offering help to conduct frequency distribution, we consider both graphs and tables as discussed below.
a). Frequency distribution table
A frequency table shows various categories of measurements and the number of observations for each. The frequency table is constructed based on the range that is divided into class intervals.
The guidelines for constructing frequency tables include using equal class widths unless there are large gaps in the data, mutually exclusive and nonoverlapping class intervals, and avoidance of open-ended classes at the lower and upper limits of the measurement scale.
The frequency distribution tables can be used for both numeric and categorical variables. A continuous variable should only be used where there is a class interval.
Examples of frequency distribution tables include:
- Grouped frequency distribution table.
- Ungrouped frequency distribution table.
- Cumulative frequency distribution table.
Depending on the nature of variables being analyzed and the research questions being answered, the frequency distribution conducted by our experts is customized into the type of tables that best achieves the study objectives.
b). Frequency distribution graphs
The information provided in a frequency distribution table can be diagrammatically illustrated using a graph. We present the frequency distribution in graphs to make the collected data easy to understand. The choice of graphical or visual representation of data depends on the nature of the variables under study. Examples of frequency distribution graphs include:
c). Bar graphs
A bar graph demonstrates data using rectangular bars of specific unchanging widths and equal spacing among them.
d). Histograms
Histograms graphically represent data using rectangular bars that vary in height. The bars are constructed in such a way that there are no spaces between them. The variable of interest is presented in the Y-axis (vertical axis) whereas the number of observations falls on the X-axis (horizontal axis).
When comparing two variant histograms each containing a different number of subjects, the cumulative percentage can be used to demonstrate the frequency when data are measured using a ratio or an interval scale.
e). Pie charts
Pie charts are graphs that present data by use of circular charts. The collected data is recorded in a circular pattern and divided into segments, each demonstrating a part of the total data.
f). Frequency polygon
A frequency polygon can be formed by joining the midpoints of the bars in a histogram. We use a straight line to connect the midpoints without displaying the bars to compare two frequency distributions in a given dataset.
4. The number of observations in a frequency table
Constructing a frequency distribution table for a dataset that has a large number of observations is guided by various basic rules. These include finding the highest and lowest values of the variables being analyzed, making a decision on the width of class intervals, and including all the possible values of the variable of interest.
After purchasing the services of a statistician for frequency distribution from us, one is assured of receiving a table with class intervals that are mutually exclusive and collectively exhaustive.
5. The number of classes
The number of classes mostly depends on the size of data, number, and magnitude of figures that need to be classified, details required, and the ease of calculation for advanced statistical modeling.
We ensure that an appropriate balance is maintained to achieve the objective of condensing the data into meaningful groups without losing important information. The number of classes mostly ranges between five and twenty with careful consideration of the factors stated above.
6. The range of the variable under study
In our frequency distribution services, we determine the range of variable data by establishing the difference between its largest and the smallest values. Accurate determination of the range allows one to create the correct number of classes. We arrange the given data in ascending order and calculate the difference between the lowest and the highest values as the computation range.
7. Class intervals
The class intervals are computed by diving the range with the number of classes rounded off to the nearest whole number. The result of the division is an equal class interval whose convenience depends on the nature of the variable being analyzed.
In situations where equal class intervals are undesirable or inconvenient, different class sizes can be used. The frequency distribution conducted by experts from our company entails assessing the dataset and the study question to determine whether equal or different sizes of class intervals are convenient.
8. The class limits
Convenient and easy-to-read class limits are used to sort the data. The first class begins with a lower limit equal to or less than the lowest value in which the observations fall. Multiples of the class interval are mostly considered for ease of comprehension among readers. Both the upper and lower class boundaries are determined with the avoidance of open-ended classes.
Those who purchase the services or a statistician for frequency distribution from our company are assured of the best help with correct computation of all relevant values. We correctly tally the number of observations into suitable class intervals while determining the relative frequency and cumulative relative frequencies where applicable.
9. The class midpoint
We calculate the class mark or midpoint by finding the sum of the upper and lower limits and dividing the result by two. The midpoint can also be found by summing up the upper and lower boundaries and diving the result by two. The frequency distribution conducted by our experts is comprehensive and ensures that all the components are correctly calculated and understandable.
10. The shape of the frequency distribution
The shape of a frequency distribution can be symmetric or asymmetric. A symmetric distribution occurs when the data are evenly distributed about the mean and resembles a bell-shaped curve when plotted, with the right portion being equivalent to the left one. For a distribution to be symmetric or unimodal, the measures of central tendency, including the mean, median, and mode are equal and can be located at the center of the distribution.
An asymmetric distribution occurs when the density of the observations is higher on either side. Such distribution can also be said to be skewed, where the majority of observations or data values lie to the left or right side of the mean.
In our help to conduct frequency distribution, we must establish whether the data is positively or negatively skewed and interpret the implications of such skewness with regard to the subject matter. We also determine the flatness and the peakedness of the distribution when deemed necessary because of the type of the study question. The height and width of frequency distributions vary with the magnitude of variability.
Carefully considering the above factors makes our company an invaluable resource to both students and researchers in different sectors who may require help to conduct frequency distribution and further statistical analyses of data.
We are available 24/7 and our customer support team is always alert to receive clients' orders, queries, facilitate work progress tracking, and quality control. Anyone wishing to hire a statistician to conduct frequency distribution can count on us for high-quality services and reliable outcomes.