Frequency Distribution Tables MCQs

Frequency Distribution Tables MCQs

Welcome to the Frequency Distribution Tables MCQs page on MCQss.com. Here, you will find a collection of interactive multiple-choice questions designed to test your understanding of frequency distribution tables.

Frequency distribution tables are essential tools in statistics for organizing and summarizing data. They provide a clear representation of how data is distributed across different categories or intervals. By constructing frequency tables, researchers and analysts can gain insights into the patterns, frequencies, and relationships within a dataset.

In order to master frequency distribution tables, it is important to understand the process of organizing and analyzing data. This includes identifying the variables of interest, determining appropriate intervals or categories, counting the frequencies, and presenting the information in a table format. Additionally, interpreting frequency distributions involves analyzing measures such as central tendency, dispersion, and shape of the distribution.

MCQss.com's Frequency Distribution Tables MCQs are designed to help you strengthen your knowledge and skills in working with frequency distribution tables. By practicing these MCQs, you can assess your understanding of key concepts, such as constructing frequency tables, calculating frequencies, and interpreting the results.

Regular practice of Frequency Distribution Tables MCQs will not only enhance your ability to construct and interpret frequency tables but also improve your overall statistical skills. These MCQs serve as a valuable resource for self-assessment, exam preparation, and reinforcing your understanding of frequency distribution concepts.

By utilizing Frequency Distribution Tables MCQs, you can develop proficiency in organizing and analyzing data, gain insights from frequency distributions, and apply these skills in various statistical analyses and research projects.

1: Preliminary Data Screening examination of frequency tables and graphs to examine data before doing the analysis of primary interest .

A.   True

B.   False

2: A list of all possible scores on a variable, along with the number of persons who received each possible score, is called _______ .

A.   Frequency distribution

B.   Hypothetical

C.   Imaginary Population

D.   Proximal Similarity

3: The _________ of cases in a group is the same as the n of cases in a group. Later in the book, n is used instead of f to report group size.

A.   Frequency

B.   Hypothetical

C.   Imaginary Population

D.   Proximal Similarity

4: F is the frequency of cases in a group .

A.   True

B.   False

5: The number of cases in a group is known as _______ .

A.   N

B.   M

C.   F

D.   E

6: A proportion is obtained by dividing the n in a group or category by the total N in the entire sample is known as _______ .

A.   Relative frequency

B.   Proportions

C.   Percentages

D.   None of these

7: Percentage is obtained by multiplying proportion by 100.

A.   True

B.   False

8: A measure of central tendency that is obtained by finding the score in a sample that has the highest frequency of occurrence is known as _______ .

A.   Percentile

B.   Rank

C.   Mode

D.   None of these

9: The cumulative percentage of scores below an X score in a frequency table can be reported as percentile rank is known as_______ .

A.   Percentile Rank

B.   Mode

C.   Binning

D.   None of these

10: Binning can create histograms or frequency tables using their own choices for number and width of bins .

A.   True

B.   False

11: Analysis options a program initially sets before a data analyst specifies any different choices is known as _______ .

A.   Percentile Rank

B.   Mode

C.   Binning

D.   Default

12: A number in a cell in an SPSS data sheet that represents a missing response is called ________ .

A.   Percentile Rank

B.   Missing Values

C.   Binning

D.   Central Tendency