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To maximize the impact of any piece of statistical work, it is important to tailor it to the right group. What kind of audience is your work aimed towards? For example, textbooks that are intended for students benefit from sections with problems and answers.
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Veröffentlichungsjahr: 2017
Content
Chapter 1: General Statistics
1.1 Explain what is Statistics?
1.2 Explain what is meant by the term Population?
1.3 What is meant by the sample?
1.4 Explain what a parameter is?
1.5 What are the methods used as Data Collection Tools in medical research?
1.6 Graphical representation (Bar, Line, Pie, Box, Scatter, Histogram)
Chapter 2: Probability
2.1 What do you understand by Probability?
2.2 What is meant by the Sample space and Event?
2.3 What is the concept of Central limit Theorem?
Chapter 3: Study Sample
3.1 What do you understand by Sampling Method?
3.2 Explain different types of study?
3.3 How to calculate sample size in a different scenario?
3.4 What do you understand by randomization and blinding in a clinical study?
3.5 How are two proportion compared between independent sample?
Chapter 4: Descriptive Statistics & Measures of Central Tendency
4.1 Describe the descriptive statistics and inferential statistics. Illustrate with an example.
4.2 Define Frequency distribution and how to calculate Mean, Median, Mode?
4.3 What do you understand by Measures of variability?
4.4 Define Range, variance, standard deviation?
Chapter 5: Distribution & Estimation
5.1 What is Normal Distribution? What does the mean of Z score?
5.2 How to identify the Outliers?
5.3 Define Skewness and Kurtosis test?
5.4 Explain what is estimation? Confidence interval, what does it mean?
5.5 How are two proportion compared between independent sample?
Chapter 6: Validity & Reliability
6.1 How data should be valid and reliable?
6.2 What is the difference between Factor & Cluster Analysis?
Chapter 7: Hypothesis Testing
7.1 What is Hypothesis testing in research methodology?
7.2 How do you determine the level of significance?
7.3 Enumerate different types of research methodologies.
Chapter 8: Correlation & Regression
8.1 How to find Correlation coefficient for categorical and non-catagorical data?
8.2 How to compute the coefficient of Linear Regression with help of analytical method?
Chapter 9: Statistical Test
9.1 Describe sensitivity and specificity as diagnostic statistical tests?
9.2 How to interpret Parametric and Non-parametric test?
9.3 Differentiate one sample, independent sample and paired sample t-test?
9.4 Describe Anova test. (One way, two way, multivariate ANOVA)
9.5 How do you find chi-square test? When is chi square test used in research?
9.6 Describe one sample Kolmogorov-Smirnov test?
9.7 Is there a difference between the number of cigarettes smoked per day between the sexes? Describe Mann-Whitney U test?
9.8 How to analyze multiple ordered data? Describe Friedman test?
9.9 Performs survival analysis and generates a Kaplan-Meier survival plot.
Chapter 10: Questionnaire Design
10.1 How to design questionnaire with Example?
10.2 How to prepare master sheet using excel?
Chapter 1: General Statistics
1.1 Explain what is Statistics?
Statistics is defined differently by different authors over a period of time. Statistics may be defined as the science of collection, presentation analysis and interpretation of numerical data from the logical analysis. It is clear that the definition of statistics by Croxton and Cowden is the most scientific and realistic one.
According to this definition there are four stages:
Collection of Data: It is the first step and this is the foundation upon which the entire data set. Careful planning is essential before collecting the data. There are different methods of collection of data such as census, sampling, primary, secondary, etc., and the investigator should make use of a correct method.
Presentation of data: The mass data collected should be presented in a suitable, concise form for further analysis. The collected data may be presented in the form of tabular or diagrammatic or graphic form.
Analysis of data: The data presented should be carefully analyzed for making an inference from the presented data such as measures of central tendencies, dispersion, correlation, regression etc.
Interpretation of data: The final step is drawing the conclusion from the data collected. A valid conclusion must be drawn on the basis of analysis. A high degree of skill and experience is necessary for the interpretation.
1.2 /1.3 Explain what is meant by the term Population? What is meant by the sample?
In a statistical inquiry, all the items, which fall within the purview of inquiry, are known as Population or Universe.
Finite population and infinite population:
A population is said to be finite if it consists of a finite number of units. Number of workers in a factory, production of articles in a particular day for a company are examples of a finite population.
A population is said to be infinite if it has an infinite number of units. For example the number of stars in the sky, the number of people seeing the Television programs etc.
Census Method: