Inferential Statistics Tests List (2023)

The following is the list of different parametric and non-parametric lists of the Inferential Statistics Tests List. A short description of each Inferential Statistics Test is also provided.

Inferential Statistics Tests: Parametric Statistics

Sr. No.Statistical TestShort Description of Inferential Test
1)Z testLarge sample test for one mean/average when sigma ($\sigma$) is known (or $n$ is large), population distribution is normal.
2)t testSmall sample test for one mean/average when sigma ($\sigma$) is unknown (and $n$ is small), population distribution is normal.
3)Z testLarge sample test for one proportion.
4)Z testSmall sample test for two means/averages when sigmas ($\sigma_1$ and $\sigma_2$) are unknown, samples are independent, and are from normal populations. The variances are NOT pooled.
5)t testSmall sample test for two means/averages when sigmas ($\sigma_1$ and $\sigma_2$) are unknown, samples are independent and are from normal populations. The variances are NOT pooled.
6)t testSmall sample test for two means/averages when sigmas ($\sigma_1$ and $\sigma_2$) are unknown, samples are independent and are from normal populations. The variances are NOT pooled.
7)t testA test for two means/averages for dependent (paired or related) samples where $d$ (The difference between samples) is normally distributed.
8)Z testLarge sample test for two proportions.
9)$\chi^2$Chi-square goodness of fit, or multinomial distribution., where each expected value is at least 5.
10)$\chi^2_{ii}$Chi-square for contingency tables (rows & columns) where each expected value is at least 5.
Either a test of independence, a test of homogeneity, or a test of association.
11)$\chi^2$Test for one variance or standard deviation.
12)F testTest for two variances or standard deviations for independent samples from the normal populations.
13)F (Anova)Test for three or more means for independent random samples from normal populations. The variances are assumed to be equal.
14)Tukey QA multiple comparison test for all pairs of means (usually for equal sample sizes).
15)Dunnett qA multiple comparison test for a control mean to other means.
16)Hartley H,
Bartlett,
Levene,
Brown-Forsythe,
O’Brien
Test for homoscedasticity, and homogeneity of variances.
17)Pearson $r$Pearson product-moment correlation coefficient.
18)SlopeTest on the slope of the linear regression line.
19)InterceptIntercept Test on the y-intercept of the linear regression line.

Inferential Statistics Tests: Non-Parametric Tests

The following is the list of non-parametric Tests with a short description of the tests.

Sr. No.Statistical TestsShort Description of Inferential Statistics Tests
1)Runs TestUsed to determine whether the sequence of data is random.
2)Mann-Whitney U TestAnalogous to Test # 5 from Parametric test list.
3)Sign TestAnalogous to Test # 2 from Parametric Test (Single sample Median Test). or Test # 7 from Parametric Test.
4)Wilcoxon Signed-Ranked TestSimilar to the sign test, but more efficient, analogous to Parametric Test # 7.
5)Kruskal-Wallis TestAnalogous to Parametric Test # 13.
6)Multiple Comparison TestAnalogous to Parametric Test # 14.
7)Spearmna $r_s$ Rank CorrelationAnalogous to Parametric Test # 15.

Advanced Inferential Statistics Tests

Following is the list of some advanced inferential Statistics tests with a short description of the test.

Sr. No. Statistical TestShort Description of Inferential Statistics Tests
1)Two-factor ANOVA With ReplicationInteraction is possible between two factors.
2)Two-factor ANOVA Without ReplicationOnly one observation per cell; no interaction effect is observed between the two factors.
3)One Datum StatUsed to compare one piece of data (datum) to a mean.
4)McNemar StAtUsed to test a 2 x 2 table of matched discordant pairs.
5)Two Poisson CountsUsed to compare two Poisson counts.
6)Two Regression SlopesUsed to compare two regression equation slopes.
7)Several Regression SlopesUsed to compare several regression equation slopes.
8)Multiple RegressionUsed to test a linear relationship with more than two variables.
9)Holgate StatisticUsed to determine spatial distribution.
Inferential Statistics Tests

Learn about Estimate and Estimation

Learn R Programming Language

Important Probability Online MCQs Test 6

This Quiz contains Probability Online MCQs Test, events, experiments, mutually exclusive events, collectively exhaustive events, sure events, impossible events, addition and multiplication laws of probability, etc. Let us start the Probability Online MCQs Test with the Answers:

Online MCQs Exam for the Post of PPSC Statistics Lecturer and Statistical Officer

1. The subset of a sample space is called

 
 
 
 

2. A conditional probability might be found in which of the following ways?

 
 
 
 

3. What is a random variable?

 
 
 
 

4. Events having an equal chance of occurrence are called

 
 
 
 

5. A fair coin is tossed 50 times, and the expected number of heads is:

 
 
 
 

6. What is a continuous random variable?

 
 
 
 

7. What is the expected value?

 
 
 
 

8. How would you calculate the probability that a random variable is less than 5?

 
 
 
 

9. $A$ and $B$ are two mutually exclusive events. The probability of $A$ happening is $\frac{1}{4}$. The probability of $BB$ happening is $\frac{1}{3}$. The probability of neither $A$ nor $B$ happening is?

 
 
 
 

10. The probability of an event happening is $\frac{1}{3}$. The probability of it not happening is?

 
 
 
 

11. In the context of probability, what is an outcome?

 
 
 
 

12. How would you describe $P(A \cap B)$ in words for two sets $A$ and $B$?

 
 
 
 

13. In the context of probability, what is a sample space?

 
 
 
 

14. What is conditional probability?

 
 
 
 

15. How would you describe $P(A|B)$ in words for two sets $A$ and $B$?

 
 
 
 

16. What shows the exact probabilities for a particular value of a random variable?

 
 
 
 

17. What word describes two events that cannot occur at the same time?

 
 
 
 

18. If $A$ and $B$ are dependent events, $P(A)=0.40$ and $P(B|A)=0.35$ then $P(A \cap B)$ is

 
 
 
 

19. $P(A\cap B() = P(A) P(B|A)$, then $A$ and $B$ are

 
 
 
 

20. What is a probability?

 
 
 
 

Probability Online MCQs Test

Probability Online MCQs Test

  • In the context of probability, what is an outcome?
  • What is a probability?
  • How would you calculate the probability that a random variable is less than 5?
  • In the context of probability, what is a sample space?
  • What word describes two events that cannot occur at the same time?
  • What is the expected value?
  • What is conditional probability?
  • What is a continuous random variable?
  • What shows the exact probabilities for a particular value of a random variable?
  • How would you describe $P(A \cap B)$ in words for two sets $A$ and $B$?
  • How would you describe $P(A|B)$ in words for two sets $A$ and $B$?
  • What is a random variable?
  • $A$ and $B$ are two mutually exclusive events. The probability of $A$ happening is $\frac{1}{4}$. The probability of $BB$ happening is $\frac{1}{3}$. The probability of neither $A$ nor $B$ happening is?
  • The probability of an event happening is $\frac{1}{3}$. The probability of it not happening is?
  • A conditional probability might be found in which of the following ways?
  • A fair coin is tossed 50 times, and the expected number of heads is:
  • If $A$ and $B$ are dependent events, $P(A)=0.40$ and $P(B|A)=0.35$ then $P(A \cap B)$ is
  • $P(A\cap B() = P(A) P(B|A)$, then $A$ and $B$ are
  • The subset of a sample space is called
  • Events having an equal chance of occurrence are called

R Language Interview Questions

MCQs Design of Experiments

This test contains MCQs Design of Experiments (DOE). Click the MCQS Design of Experiments list links to start with the quiz. All the MCQs Designs of Experiments are from topics of Basic principles of Design of Experiments, concept of Randomization, Replication, types of Designs, Experimental Unit and Error, CRD, CRBD, LSD, Greco LSD, Factorial design and experiments, Response surface design, and balanced incomplete block designs. etc.

Online MCQs Design of Experiments

Design of Experiments Quiz 8Design of Experiments Quiz Questions 7
MCQs DOE 6MCQs DOE 5MCQs DOE 4
MCQs DOE 3MCQs DOE 2MCQs DOE 1

An experiment deliberately imposes a treatment on a group of objects or subjects to observe the response. The experimental unit is the basic entity or unit on which the experiment is performed. It is an object to which the treatment is applied and the variable under investigation is measured and analyzed.

Single-Factor Design: In a single-factor experiment only a single factor varies while all others are kept constant. The CRD, RCBD, and LSD are examples of single-factor designs.

Multi-Factor Design: Multi-factor designs are also known as factorial experiments. When several factors are investigated simultaneously in a single experiment, known as factorial experiments.

Systematic Designs: In systematic designs treatments are applied to the experimental units by some systematic pattern, i.e., by the choice of the experimenter. For example, the experimenter wishes to test three treatments and he decides to have four repetitions of each treatment.

Online MCQs Design of Experiments

Randomized Designs: In randomized designs, as the treatments are applied randomly, therefore the conclusions drawn are supported by statistical tests. In this way, inferences are applicable in a wider range and the random process minimizes the systematic error. The analysis of variance techniques is also suitable for randomized designs only.

The purpose of the Design of Experiments is:

  • Get maximum information for minimum expenditure in the minimum possible time.
  • Helps to reduce the experimental error.
  • To ignore spurious effects, if any.
  • To evaluate and examine the outcomes critically and logically.
https://itfeature.com

Computer MCQs

Learn R Programming