Basic Concepts in Statistics

This document provides an overview of the basic concepts in statistics. It covers topics such as measurement levels, classifying numbers as discrete or continuous, identifying independent and dependent variables, and different types of variables. The document includes activities and tables for better understanding. References are also provided.

Running head: BASIC CONCEPTS IN STATISTICS
BASIC CONCEPTS IN STATISTICS
Name of the student:
Name of the university:
Author note:

1BASIC CONCEPTS IN STATISTICS
Table of Contents
Activities..........................................................................................................................................2
Activity 1: Classifying each as either nominal, ordinal, interval or ratio level of measurement 2
Activity 2: Classifying whether the number obtained in the following is discrete or continuous
.....................................................................................................................................................3
Activity 3: Identifying the independent and dependent variables...............................................4
Activity 4: Identifying the independent, dependent, moderator, control and mediator variable/s
.....................................................................................................................................................5
References........................................................................................................................................6

2BASIC CONCEPTS IN STATISTICS
Activities
Activity 1: Classifying each as either nominal, ordinal, interval or ratio level of
measurement
1. Nominal 9. Ratio
2. Nominal 10. Nominal
3. Ordinal 11. Nominal
4. Nominal 12. Nominal
5. Ordinal 13. Nominal
6. Ordinal 14. Nominal
7. Nominal 15. Ordinal
8. Ratio
Table 1: Classification Based on Nominal, Ordinal and Ratio Level of Measurement
(Source: Rastogi et al. 2015)

3BASIC CONCEPTS IN STATISTICS
Activity 2: Classifying whether the number obtained in the following is discrete or
continuous
1. Discrete 9. Continuous
2. Continuous 10. Discrete
3. Discrete 11. Discrete
4. Discrete 12. Discrete
5. Continuous 13. Continuous
6. Discrete 14. Continuous
7. Discrete 15. Continuous
8. Discrete
Table 2: Identification of Discrete or Continuous Numbers
(Source: Rapp et al. 2015)

4BASIC CONCEPTS IN STATISTICS
Activity 3: Identifying the independent and dependent variables
Item Independent Variable/s Dependent Variable/s
1 Scholastic and non-scholastic factors Academic performance
2 Modern technology Students’ academic performance
3 Personal and professional
characteristics of
presidents of State Universities
Relationship
4 Basic Education Curriculum (K to
12)
Effects
5 Female and male students Math performance
6 Student’s class participation in an
English class
Questioning techniques
7 Teacher shortage Poor students’ academic
performance
8 Influence of parents’ involvement Academic performance of children
9 Effect of everyday graded recitation Motivation, engagement and
achievement of freshmen students
10 High and low self-efficacy The levels of intrinsic motivation of
students
Table 3: Identification of Independent and Dependent Variables
(Source: Berssaneti and Carvalho 2015)

5BASIC CONCEPTS IN STATISTICS
Activity 4: Identifying the independent, dependent, moderator, control and mediator
variable/s
1. Moderating 6. Independent
2. Dependent 7. Dependent
3. Mediating 8. Mediating
4. Mediating 9. Control
5. Dependent 10. Dependent
Table 4: Identification of Different Types of Variables
(Source: Smoktunowicz et al. 2015)

6BASIC CONCEPTS IN STATISTICS
References
Berssaneti, F.T. and Carvalho, M.M., 2015. Identification of variables that impact project
success in Brazilian companies. International Journal of Project Management, 33(3), pp.638-
649.
Rapp, M., Bassok, M., DeWolf, M. and Holyoak, K.J., 2015. Modeling discrete and continuous
entities with fractions and decimals. Journal of Experimental Psychology: Applied, 21(1), p.47.
Rastogi, R., Mondal, P., Agarwal, K., Gupta, R. and Jain, S., 2015. GA based clustering of
mixed data type of attributes (numeric, categorical, ordinal, binary and ratio-scaled). BVICA M's
International Journal of Information Technology, 7(2), p.861.
Smoktunowicz, E., Baka, L., Cieslak, R., Nichols, C.F., Benight, C.C. and Luszczynska, A.,
2015. Explaining counterproductive work behaviors among police officers: The indirect effects
of job demands are mediated by job burnout and moderated by job control and social support.
Human Performance, 28(4), pp.332-350.