Question:

1: Inconsistent Responses in the Data Editing phase of preparing Data for Quantitative Data Analysis is Responses that are not in harmony with other information

2: Descriptive Measure that is computed from a Sample is called a Statistic.

3: Is a Standard Deviation of 10 a large number indicating great variability, or is it small number indicating little variability? To answer this question correctly, one should look carefully at the value of the Coefficient of Variation.

4: Expressed in Percentiles, the Interquartile Range is the difference between the 25th and 75th Percentiles. It is true.

5: In Hypothesis Testing the Probability of failing to reject the Null Hypothesis given that the Alternative Hypothesis is actually true is known as the Type II Error.

6: Which of the following alternatives is possibly the Dependent Variable in a study in which Regression Analysis is used to analyses the data?  The disposable income of the respondent.

7: ANOVA is used to determine if a Non-Metric Variable influences a Metric Variable. True

8: Which test could best be used to test the hypothesis that the average price that people are willing to pay for a meal at the University restaurant differs between Dutch, German and Chinese students? ANOVA.

9: What is the appropriate method to test if having a mobile phone is related to gender? T-test.

10: The objective of Regression Analysis is to explain a Dependent Variable based on 1 or more independent variables. True

Each of the following is a form of doing organizing your data into a table

Percentiles are Values that are not specified in the coding instructions

Statistical inference is the process of making an estimate, prediction, or decision about a Population based on Sample Data.

Correlation is a measure of the “Degree of Relatedness” of two Variables.

Multiple regressions analysis measures the effect of an Independent Variable on the Dependent Variable, while the other independent variables are held constant.

a) Descriptive Statistics and Inferential Statistics play an important role but there is a difference between them. Descriptive statistics helps in describes the statics related to population and inferential statistics is used to make the generalization from the samples designed. Descriptive Statistics is more about analyzing the situation where as inferential statistics focuses on drawing the conclusion from the observation. In case of descriptive Statistics the final output is shown in the form of tabular form where as in case of inferential statistics the final outcome is in the form of probability. The scenario is described in case of descriptive statistics but inferential statistics helped in finding the probability of occurrence of event. Descriptive statistics helps in explaining the overall summary gained from the sample and learning about from the actual facts and figures.

• Analytical Method- This method covers all the process that is used to make comparison between different identities and finding the correlation between them. This includes correlation, regression analysis and association of analysis. This is used to deal with actual fact and figures.
• Inductive method- This covers the procedures that are used to generalize the overall process by estimating the pros and cons. This method overs several processes like interpolation, extrapolation and various theories of probability. They analyses the available facts and figures so that a productive decision could be made.

McQs

These methods include some common step that is collecting the data, organizing it, exploring the information and then presenting the outcome in a specific trend or pattern.

b) It is rightly said that, the most important descriptive measure is the sample standard deviation. This can be said by considering the implication of its size in relation to the sample statistics that indicates inferential statistics is worthwhile. It can be treated as a best method as it considers all the data that is dependent on different characteristics.  It checks the maximum deviation and the extent to which change occur. It considers all the observations by checking the future mathematical statement. It makes sure that fluctuation does not affect the sampling. It is true that data may fall into symmetrical form or asymmetrical form but standard deviation makes in finding out the inference from all the distribution.

Standard deviation is best way to measure the variation and then checking the fluctuation for measuring the dispersion. It is used for further statistical work and checking the deviation. For example, in computing skewness and finding out the correlation we make use of standard deviation. When there is an option to select one of the descriptive method standard deviation is used as it helps in bringing out best analyzed result. It helps in showing the actual data that is clustered around a mean value and also gives a more accurate idea that do not affect the extreme values. Thus, standard deviation can be choose for performing descriptive study. It also helps in calculating the data points so that good estimation can be done of all the normal data set.

c) It can be stated that standard deviation plays an important role in the Inferential Statistical Model of Empirical Rule as it helps in measuring the average amount of variability. The standard deviation also helps in finding out the dispersion in the model. It is used in empirical rule as it squares the number and makes the negative result positive. It is significant as it shows the central tendency. It supports the model by judging the actual returns and risks by determining the average performance and outcome in a particular area. Apart from that, standard deviation helps in bringing out the outcome by measuring the central tendency and also measuring the spread rate. In inferential statistics standard deviation plays an important role as it estimates the parameters and also tests the statistical hypotheses.

The role standard deviation in determining the Precision of the model is finding out the random errors from the solution. It helps in measuring the statistical variability in the solution so that absolute value can be found. It helps to clarify the distribution of the mean and other outliers that may be present. It helps in finding out that the data is close to the result so that data can be spread over wide range. It also helps in testing the precision and accuracy of the result so that change can be done. It also monitors the information and helps in data acquisition and selection of the best result.

References

van den Besselaar, Peter, “Descriptive Statistics, Inferential Statistics, Rhetorical Statistics” (2018) 54(11) Journal of the American Society for Information Science and Technology

YENSEN, JACK, “Complete Report Of Descriptive And Inferential Statistics Requested” (1979) 28(2) Nursing Research