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Contents of Mathematics and Statistics Degree in: Biosciences and Biotechnology 2014/2015 Teacher: Nadaniela Egidi MATHEMATICS Set theory. The sets and the operations between them. The De Morgan’s laws. The numerical sets: N, Z, Q, R. The real line, bounded or unbounded intervals, neighbourhoods. The union, intersection, difference between sets, the complement of a set. Functions. The domain, the codomain and the image of a function. The injective, surjective and bijective functions. The composition of functions, the inverse function. The graph of a function. The monotone functions. Increasing, strictly increasing, decreasing or strictly decreasing functions and their properties. The even functions and the odd functions. The elementary functions. The n-th power function and the n-th root function. The exponential function and its properties. The logarithm function and its properties. The absolute value function, linear functions and their properties. Graphs of elementary functions The trigonometric functions. The angles, their radian measure and their graphical representation. The periodic functions, the trigonometric functions: sin(x), cos(x), tan(x), cot(x), arcsin(x), arccos(x), arctan(x), arccot(x). The fundamental properties of trigonometric functions. Limits of functions. Limits of functions, right-hand limit and left-hand limit. Limits of elementary functions. Theorem on uniqueness of the limit. Limits of power functions, root functions, exponential functions, logarithmic functions, trigonometric functions. Operations and limits. Indeterminate forms and some techniques to solve them. Notable special limits. Significant limits that converge to the Euler number. Significant limits involving trigonometric functions. The orders of infinity. Indeterminate forms where the base tends to infinity and the exponent tends to zero. Sequences and limits. Definition and examples of sequences, subsequence. Limit of a sequence. Convergent, divergent or indeterminate sequences. Properties of sequences. The continuous functions. Definition of a continuous function at a point and on an interval. Properties of continuity, examples of continuous functions, examples of functions that are not continuous. The intermediate zero, the Weierstrass theorem, the bisection method. 1 The derivatives. Newton’s difference quotient, the definition of derivative and notations used in the differentiation. Left derivative and right derivative. Derivatives of the elementary functions. The derivation rules of a product and of a quotient. The chain rule formula, the derivative of the inverse function. Examples of functions that are not differentiable. Higher order derivatives, Rolle’s theorem, Lagrange’s theorem and De L'Hopital’s theorem. Applications of the De L'Hopital’s theorem to some significant limits, the treatment of some indeterminate forms. Geometrical meaning of the derivative and the equation of the tangent line to the graph of a function, the derivative of the inverse function of a given function. The study of function. Determination of the domain of a function. Determination of the sign of a function and the intersections of the graph of the function with the coordinate axes. Limit of a function, horizontal, vertical and oblique asymptotes. Maximums and minimums of a function that are relative or absolute. Correlations between the first derivative of a function and the maximums, the minimums, or monotonicity of the function. Concave functions and convex functions in a range, inflection points of a function. Link between the second derivative of a function to its concavity and its inflections. Conditions sufficient to obtain the maximum or minimum for a function. The integral calculus. Definite integral: geometric meaning, definition, additive property, linear property and comparison between integrals. The theorem of the mean value. The integral function. The fundamental theorem of calculus. Primitives and properties. Indefinite integrals and properties. Fundamental formula of integral calculus. Well known indefinite integral. Integration by substitution. Integration by parts. Improper integrals with unbounded domain or unbounded integrating function. Differential equations. Linear differential equations of the first order. Cauchy problem for linear differential equations of the first order, existence and uniqueness of the solution. First order differential equations with separable variables. Bernoulli differential equation. Second order linear differential equations with constant coefficients, the solution of the associated homogeneous equation, and looking for particular solutions. Cauchy problem for linear differential equations of second order with constant coefficients. 2 STATISTICS Descriptive Statistics. Content, purpose, components and terminology in Statistics. The phases of the statistical survey Measurements scales (nominal, ordinal, interval, ratio) and data types. Organization of qualitative or quantitative (discrete or continuous) raw data in tables of frequency distribution. Graphical representation of frequency distribution: bar charts, pie charts, histograms, frequency polygons. Measures of central tendency of variability and of shape: mean, geometric mean, quadratic mean, harmonic mean, median, mode, mid-range, qquantile. Measures of variability: range, mean absolute deviation, median absolute deviation, variance, sample variance, standard deviation, sample standard deviation, coefficient of variation, moment of order k. Measures of shape: symmetry, kurtosis. Probability. Random experiment and event. Probability: frequentist definition, subjective definition, classical definition and axiomatic definition. Probability theory: sample set, opposite event, union event, intersection event, axioms. Theorem of the probability of the union event, conditional probability, statistically independent events, Bayes’ theorem. Elementary combinatorics. Permutation of n, k-permutation of n, k-combination of n, the binomial coefficients. Discrete probability distributions. Probability distribution of a discrete random variable: mean, variance, cumulative distribution function. Discrete uniform distribution, binomial distribution, multinomial distribution, Poisson distribution, hypergeometric distribution. Continuous probability distributions. Probability distribution of a continuous random variable: probability density function, cumulative distribution function, mean, variance. Continuous uniform distribution, negative exponential distribution, normal distribution, Student’s t-distribution, chi-square distribution, standard normal distribution. Law of large numbers, central limit theorem. A practical use of the standard normal distribution. Tables for standard normal distribution, Student’s t-distribution, chi-square distribution. Statistical inference. Population, sample, parameter and statistics. Sampling distributions: sampling distribution of the mean; sampling distribution of the sample variance; sampling distribution of the sample proportion; sampling distribution of 3 the difference between means; sampling distribution of the difference between proportions. Interval estimate of a population parameter: confidence interval for a mean; confidence interval for a proportion; confidence interval for a difference between means; confidence interval for a difference between proportions. Statistical hypothesis test: two-tailed test, one-tailed test on the left, one-tailed test on the right, errors of type I and type II, hypothesis test for a mean, hypothesis test for a proportion, hypothesis test for a difference between means, hypothesis test for a difference between proportions. 4