PAU Applied Mathematics for Social Sciences II - Canary Islands / ULPGC & ULL study materials
PAU Applied Mathematics for Social Sciences II - Canary Islands / ULPGC & ULL study resources

PAU Applied Mathematics for Social Sciences II - Canary Islands / ULPGC & ULL study plan

PAU Applied Mathematics for Social Sciences II - Canary Islands / ULPGC & ULL · Give each week a clear focus.

8 weeks · About 6 hours per week

Week 1

Matrices and systems of linear equations: matrix operations, rank, determinants, Gaussian elimination, Rouché–Capelli discussion, Cramer's rule, matrix equations

  • Compute sums, products, transposes and powers of 2×2 and 3×3 matrices by hand and state when a product is defined

  • Calculate determinants of order 2 and 3 using cofactor expansion and apply the properties of determinants to simplify before computing

  • Determine the rank of a matrix by row reduction and identify inconsistent or dependent rows at a glance

  • Solve square systems with Cramer's rule and check the answer by substitution

Your checkpoint

A one-page handwritten summary sheet with 12 solved exercises (3 per goal) covering matrix products, 3×3 determinants, rank and Cramer's rule, each with a final verified answer.

Week 2

Matrices and systems of linear equations: matrix operations, rank, determinants, Gaussian elimination, Rouché–Capelli discussion, Cramer's rule, matrix equations

  • Apply Gaussian elimination to classify a system as compatible determined, compatible indeterminate or incompatible

  • State and use the Rouché–Capelli theorem comparing rank of the coefficient matrix with rank of the augmented matrix

  • Solve matrix equations of the form AX = B and XA = B by inverting A and justify when the inverse exists

  • Discuss one-parameter systems and express the solution set in terms of the free parameter

Your checkpoint

A written solutions set of 8 systems, at least 3 of them depending on a parameter, each with an explicit Rouché–Capelli discussion and the full solution set written out.

Week 3

Linear programming: modelling with inequalities, feasible region, vertices, graphical and algebraic optimisation, duality and sensitivity in two-variable problems

  • Translate a word problem in two variables into a system of linear inequalities and identify the objective function

  • Draw the feasible region accurately, label every vertex and detect unbounded or empty regions

  • Evaluate the objective function at the vertices and apply the fundamental theorem of linear programming to locate the optimum

  • Recognise integer or excluded-boundary constraints and adjust the vertex search accordingly

Your checkpoint

A graphical portfolio of 6 complete linear programming problems on squared paper, each with the feasible region shaded, all vertices labelled with coordinates and the optimal value stated with justification.

Week 4

Linear programming: modelling with inequalities, feasible region, vertices, graphical and algebraic optimisation, duality and sensitivity in two-variable problems & Limits, continuity and differentiation: limits and indeterminacies, asymptotic behaviour, continuity, derivative rules, tangent line, rates of change

  • Solve two-variable linear programming problems algebraically by intersecting constraint lines instead of relying on the drawing

  • Interpret the dual problem and the shadow price of a binding constraint in a small two-variable model

  • Analyse how the optimal vertex changes when one coefficient of the objective function varies, and state the range of optimality

  • Compute limits of rational and piecewise functions at a point, resolving 0/0 and ∞/∞ indeterminacies

Your checkpoint

A timed 60-minute mock section with 2 full linear programming problems (including one sensitivity question) and 4 limit computations, self-marked against a written rubric with errors logged.

Week 5

Limits, continuity and differentiation: limits and indeterminacies, asymptotic behaviour, continuity, derivative rules, tangent line, rates of change

  • Resolve the indeterminacies 0/0, ∞/∞, ∞−∞ and 0·∞ using factorisation, conjugates, common denominators and L'Hôpital's rule

  • Determine asymptotic behaviour, horizontal and vertical asymptotes and one-sided limits at the boundary of the domain

  • Decide continuity of a function at a point and find the value of a parameter that makes a piecewise function continuous

  • Differentiate using the product, quotient, chain and implicit rules, and write the tangent line at a given point

Your checkpoint

A formula-and-technique card listing each indeterminacy with one worked example, plus 10 differentiation and tangent-line exercises solved end to end.

Week 6

Applications of the derivative: monotonicity, extrema, concavity and convexity, inflection points, curve sketching, optimisation of one-variable economic functions

  • Find intervals of increase and decrease from the sign of the first derivative and classify extrema

  • Determine concavity, convexity and inflection points from the sign of the second derivative

  • Sketch a complete curve from its domain, asymptotes, monotonicity and concavity without plotting software

  • Optimise one-variable economic functions such as cost, revenue and profit, and interpret the marginal values at the optimum

Your checkpoint

Two full curve sketches with a written analysis table (domain, asymptotes, first-derivative sign chart, second-derivative sign chart) plus one solved profit-maximisation word problem.

Week 7

Integration: antiderivatives, definite integrals, Barrow's rule, area between curves, accumulation and applied interpretation & Probability: sample space, combinatorics, conditional probability, independence, total probability, Bayes' theorem

  • Compute immediate integrals of elementary functions and apply integration by substitution and by parts where required

  • Apply Barrow's rule to evaluate definite integrals and compute the area between two curves, including finding the intersection points

  • Solve counting problems using permutations, combinations and the multiplication principle

  • Apply conditional probability, independence, the total probability theorem and Bayes' theorem to a stated problem

Your checkpoint

A mixed problem set of 10 exercises (6 on integration and areas, 4 on probability including one full Bayes tree diagram) solved with all intermediate steps shown.

Week 8

Random variables and distributions: discrete and continuous variables, expectation and variance, binomial and normal distributions, approximation and standardisation & Probability: sample space, combinatorics, conditional probability, independence, total probability, Bayes' theorem

  • Distinguish discrete from continuous random variables and compute expectation and variance from a table or a density function

  • Compute binomial probabilities and identify when the binomial model applies

  • Standardise a normal variable, use the standard normal table and compute probabilities for intervals and inverse problems

  • Decide when the normal approximation to the binomial is valid and apply the continuity correction

Your checkpoint

A full timed mock exam of 6 problems spanning all seven domains, marked against a score breakdown per domain, with a written list of the three weakest areas and the corrections made.

Milestones

Week 2: Solve a parameter-dependent 3×3 system unaided, correctly stating the Rouché–Capelli discussion and writing the solution set in under 15 minutes.

Week 4: Score at least 70% on the timed mock section covering linear programming and limits, with no arithmetic errors in the vertex coordinates.

Week 6: Produce a complete curve sketch with correct monotonicity and concavity intervals and solve one economic optimisation problem without consulting notes.

Week 8: Score at least 60% overall on the full mock exam with no domain below 40%, and have every logged error rewritten correctly.