eChapters

4.1 Write True/False

4.1.1 Preliminaries

Q.1    In selection of a test, one should try to keep the probabilities of both types of error small.
Q.2    Under a non-sequential sampling scheme (i.e. fixed sample size n), it is not possible to minimise both the errors at the same time.

3.1  Write True/False

Q.1    The estimates obtained though various methods of point estimation, in general, do not concide with the true values of the parameters.
Q.2    The statistician is interested in finding an ‘interval’ within which the true value of the parameter θ is expected to lie with certain ‘confidence coefficient’, say (1 – α).

2.1  Write True/False

Q.1    From theoretical point of view, the most general method of estimation is the “Maximum Likelihood Estimation Method.”
Q.2    The method of “maximum Likelihood Estimation” was initially formulated by the statistician named as “C.F. Gauss.”

1.1 Write True/False

Q.1    The process of knowing all the relevant information from the known sample to the unknown population, is known as “Statistical Inference.”
Q.2    An enquier may be completely unknown to some feature of the population but he may want to guess completely about that feature based on a random sample drawn from the population. This type of problem is known as the “Problem of Estimation.”

True/False

Q.1.    The precision of an estimator increases as the sample size increases.
Q.2.    Statistical power is the probability that a statistical test will indicate a significant difference is true i.e. it is the probability of taking correct decision.

True/False

Q.1.    In many clinical research studies, the regression analysis is used to develop models for prediction of an outcome from one or more explanatory variables.
Q.2.    Now a days, the linear, logistic and Cox (proportional hazards) regression models are used frequently in medical research.

True/False

Q.1.    Demographic data and vital statistics are important tools for researchers, epidemiologists, health planners and health professionals.
Q.2.    The distribution of people across different geographic regions is known as population density.

True/False

Q.1.    The accuracy of the measurement refers to how close the measured value is to the true value.
Q.2.    The precision refers to how close a set or group of measurements are together.
Q.3.    If the processes of measurement are repeated under identical condition, then precision explains that up to what extent these repeated values are reliable.

True/False

Q.1.    In many epidemiological studies with substantial follow up time, it is very often an interest to study the time taken for a particular event to occur.
Q.2.    The time taken for death or graft failure since transplant, time taken for relapse after treatment, time to death after treatment etc. are examples for survival time.

True /False

Q.1.    A diagnostic test enables the doctors to reach at a decision whether the patient is suffering from a particular disease or not.
Q.2.    The recent developments in the field by biotechnology have led to the development of many new medical tests.
Q.3.    The general principles in designing and conduct diagnostic test studies are not known well.

True/False

Q.1.    In clinical practice and in public health, the objective is to find better ways to ‘prevent,  diagnose and treat disease’.
Q.2.    Among all research designs, experimental study designs are the most reliable and  ideal designs to evaluate the ‘effectiveness or value’ of interventions (like drugs,  medication etc.) for human disease and disabilities.

True/False

Q.1.    The purpose of most medical research is to identify the causes of disease and search out the ways to prevent or cure them.
Q.2.    Now a day, epidemiology has become a basic science for public health
Q.3.    The studies of diagnostics therapeutic and prognostic procedures have successfully incorporated into growing stream of “Clinical Epidemiology”.

True/False

Q.1.    Two independent random variables (X,Y) are always uncorrelated but reverse may not be true

True/False

Q.1.    The most fundamental assumption for “Parametric inference” is that the random sample drawn is from “Normal” population.
Q.2.    The most fundamental assumption of “Non-parametric” test is that the random sample drawn is from “Continuous distribution”
Q.3.    The standard parametric methods are applicable for “Estimating the parameter” as well as for “Testing the hypothesis” about the parameters.
Q.4.    Non-parametric methods, are applicable only for testing the hypothesis about  distribution but not applicable for estimation purpose of parameter.

True/False

Q.1.    Qualitative or categorical data are frequently collected in medical investigation.
Q.2.    Qualitative variables may be, e.g. sex, blood type, treatment, groups, classification of exposure or disease and patients survived or not.
Q.3.    Qualitative variables include the grouped quantitative variables such as age groups of mothers, pre term babies, birth weight groups, 
hypertensive or normotensive etc.

True/False

Q.1.    According to Prof. RA Fisher “ANOVA” is the separation of variance assignable to one group of causes from the variance assignable to other group of causes.
Q.2.    The basic purpose of ANOVA technique is to test the equality (homogeneity) of several population means from the same 
experiment.

True/False

Q.1.    A hypothesis that sets the fundamental objective of scientific study is called the “Research hypothesis”.
Q.2.     A statistical assumption or statement about the unknown parameters of a population is known as Statistical hypothesis.

True/False

Q.1.    The process of knowing all the relevant information from the known sample to the unknown “Population parameter” is known as “Statistical inference.”
Q.2.    The method of estimating the unknown parameter of the population on the basis of known sample values is known “Estimation method.”
Q.3.    The “Point estimation and Interval estimation” are the two methods of estimating the unknown parameters of the population.

True/False

Q.1.    Collectivity (totality) of all sampling units is known as the “Population” and population size is denoted by “N”.
Q.2.    A list of all sampling units with their identification is known as “Sampling frame”. For example a list of all newly-born children in maternity home during a period of three months with specification of their sex, weight, name of their parents, their permanent address, etc. is known as sampling frame.
Q.3.    A function of all sampling units in the population is known as population parameter or population constant.

True/False

Q.1.    The set of all possible outcomes of a variable along with the frequency (the number of occurrence) of each outcome or a group of outcome is called “Frequency Distribution”.
Q.2.    The frequency of an occurrence of each outcome of a trail divided by total frequency is known as “Relative frequency” of the outcome.
Q.3.    The distribution of total probability “1” into probabilities of occurrence of each outcome of a trial, is known as probability distribution of the outcome.