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General Aptitude & Oceanography

Latest questions in this category.

25 questions

What does the term 'longitudinal study design' mean?

Longitudinal designs collect repeated measurements from same subjects over months or years, enabling assessment of temporal trends, incidence and causal direction. This contrasts cross-sectional designs capturing single time point. Longitudinal approaches track developmental changes, disease progression or intervention effects across distinct follow-up period.

Ref: Kothari, Research Methodology Methods and Techniques, 4th Multi-coloured Edition, Chapter 3 Research Design, defines longitudinal studies as repeated observations over distinct time period to track changes and incidence, published by New Age International Publishers.

What is the best way to minimize the chances of a type-I error in a diagnostics test?

Type-I error corresponds to false positive, rejecting true null, claiming disease when absent. Increasing specificity raises true negative rate, directly lowering false positives defined as 1-specificity. Sensitivity controls type-II false negatives, while prevalence changes predictive values, not intrinsic error rates of test itself.

Ref: Lehmann and Romano, Testing Statistical Hypotheses, 4th Edition, Chapter on Diagnostic test errors, explains type I error false positive rate equals one minus specificity minimized by improving specificity, published by Springer Verlag New York.

Which of the following mean is not used to report measure of central tendency?

Arithmetic mean averages values directly, geometric mean multiplies and root-transforms suitable for ratios, harmonic mean reciprocally averages rates. Relative mean is not a recognized statistical central tendency measure. Researchers report appropriate mean based on distribution scale, not relative mean terminology.

Ref: Pagano and Gauvreau, Principles of Biostatistics, 2nd Edition, Chapter on Descriptive Statistics Measures of Central Location, lists arithmetic geometric harmonic means as valid averages excluding relative mean terminology, published by Duxbury Brooks Cole Publishing.

The reporting of results is preferred to report with confidence intervals (CIs) as compared to pvalue because:

Confidence intervals provide point estimate plus precision range and indicate whether null value is excluded, conveying both clinical significance and statistical significance. P-values only give dichotomous probability of observed data under null without information on effect magnitude or uncertainty, making CIs far more informative.

Ref: Armitage, Berry and Matthews, Statistical Methods in Medical Research, 4th Edition, Chapter 5, describes advantages of confidence intervals providing significance variability magnitude over p-values alone, published by Blackwell Science Oxford.

Which of the following is a method of integrating the findings of prior research studies using statistical procedures?

Meta-analysis statistically combines effect sizes from multiple independent studies addressing same question, increasing power and precision, assessing heterogeneity via forest plots and I-squared. Unlike secondary analysis which reuses data or content analysis which codes themes, meta-analysis quantitatively synthesizes prior research.

Ref: Cochrane Handbook for Systematic Reviews of Interventions, Version 6.3, Chapter 10 Analysing Data, defines meta-analysis as statistical integration of effect sizes from prior studies pooling results quantitatively, published by Cochrane Collaboration and Wiley Blackwell.

Non-parametric data is best represented by:

Non-parametric or skewed data violate normality assumptions, so mean and standard deviation become misleading influenced by outliers. Median provides robust central tendency and interquartile range shows spread of middle 50% observations, resisting extreme values, making them preferred summary statistics for such distributions.

Ref: Rosner, Fundamentals of Biostatistics, 8th Edition, Chapter 2 Descriptive Statistics, states non-parametric skewed data summarized best with median and interquartile range rather than mean standard deviation, published by Cengage Learning Brooks Cole.

What type of bias is reduced by randomisation?

Randomization assigns participants to groups by chance, ensuring both measured and unmeasured prognostic factors distribute equally on average. This minimizes selection bias and confounding, balancing baseline characteristics. While blinding reduces ascertainment bias and trial registries reduce publication bias, randomization specifically targets selection.

Ref: Friedman, Furberg and DeMets, Fundamentals of Clinical Trials, 4th Edition, Chapter 6 Randomization, explains elimination of selection bias through random allocation balancing prognostic factors, published by Springer Science Business Media.

Specificity of a test:

Specificity equals true negatives divided by true negatives plus false positives, representing true negative rate. High specificity means few false positives, crucial for ruling in disease. It contrasts sensitivity, which identifies diseased patients, and directly complements false positive rate as one minus specificity.

Ref: Park, Park's Textbook of Preventive and Social Medicine, 26th Edition, Chapter on Screening methods, defines specificity true negative rate ability to identify healthy persons correctly, published by Banarsidas Bhanot Publishers Jabalpur India.

The mean, median, mode of a data set are 135, 133 and 130, respectively. The distribution of the data set is:

In skewed distributions, relationship is generally mean vs median vs mode. For positively right-skewed data, tail extends to higher values pulling mean above median above mode. Here 135 greater than 133 greater than 130 fits that pattern, indicating positive skew, unlike symmetrical where all equal.

Ref: Daniel, Biostatistics: A Foundation for Analysis in the Health Sciences, 10th Edition, Chapter 2 Describing Data, describes skewness relationship mean median mode positively skewed distribution mean greater than median greater than mode, published by Wiley.

A scientist is weighing each of 30 fishes. Their mean weight worked out is 30 gm and a standard deviation of 2 gm. Later

Adding constant 2 gm to every measurement shifts location parameter but not dispersion. Mean increases by constant to 32 gm, while standard deviation which depends on differences from mean remains unchanged at 2 gm, because variance of X+c equals variance of X.

Ref: Gupta, Fundamentals of Statistics, 7th Edition, Chapter on Measures of Central Tendency and Dispersion, explains effect of adding constant on mean and variance invariance of standard deviation, published by Himalaya Publishing House Mumbai.

Emmanuelle Charpentier and Jennifer A. Doudna have been awarded the Nobel Prize in Chemistry in 2020 for their work on:

Charpentier and Doudna elucidated bacterial adaptive immune mechanism and repurposed it into programmable genome editing tool. Their CRISPR-Cas9 system uses guide RNA to direct Cas9 nuclease creating double-strand breaks at targeted loci, revolutionizing molecular biology and therapeutics, recognized by 2020 Chemistry Nobel.

Ref: Alberts et al., Molecular Biology of the Cell, 6th Edition, Chapter 8, discusses CRISPR-Cas9 bacterial immunity adaptation, genome editing mechanism, Charpentier and Doudna Nobel Chemistry 2020 contributions, published by Garland Science.

Similarity index is useful for assessing:

Similarity index generated by software like Turnitin, iThenticate or Urkund quantifies percentage of textual overlap between submitted manuscript and existing databases. High similarity suggests potential uncredited copying, aiding editors and universities to screen plagiarism, though it does not judge intent, merely textual matching.

Ref: Bailey, Academic Writing: A Handbook for International Students, 4th Edition, Chapter on Research Integrity, discusses similarity index plagiarism detection software Turnitin iThenticate and ethical writing, published by Routledge Taylor and Francis Group.