analyse 5
GRADE 5
Supporting 5 3(B) multiply with fluency a three-digit number by a two-digit number using the standard algorithm 2 Supporting 5 3(C) solve with proficiency for quotients of up to a four-digit dividend by a two-digit divisor using strategies and the standard algorithm 2 Supporting 5 3(D) represent multiplication of decimals with products to the |
Basic Analysis I
Analysis is the branch of mathematics that deals with inequalities and limits The present course deals with the most basic concepts in analysis The goal of the course is to acquaint the reader with rigorous proofs in analysis and also to set a firm foundation for calculus of one variable (and several variables if volume II is also considered) Ca |
MATHEMATICAL FOUNDATIONS
Mathematical Foundations for Data Analysis is a book by Jeff M Phillips that introduces the essential mathematical concepts and tools for data science It covers topics such as probability linear algebra optimization and dimensionality reduction with examples and exercises The book is available as a free PDF download |
0.2 About analysis
Analysis is the branch of mathematics that deals with inequalities and limits. The present course deals with the most basic concepts in analysis. The goal of the course is to acquaint the reader with rigorous proofs in analysis and also to set a firm foundation for calculus of one variable (and several variables if volume II is also considered). Ca
0.3 Basic set theory
Note: 1–3 lectures (some material can be skipped, covered lightly, or left as reading) Before we start talking about analysis, we need to fix some language. Modern * analysis uses the language of sets, and therefore that is where we start. We talk about sets in a rather informal way, using the so-called “naïve set theory.” Do not worry, that is wha
+ c + c2 + + cn = : 1 c
Proof: It is easy to check that the equation holds with n = Suppose it is true for ocw.mit.edu
1.2.2 Archimedean property
As we have seen, there are plenty of real numbers in any interval. But there are also infinitely many rational numbers in any interval. The following is one of the fundamental facts about the real numbers. The two parts of the next theorem are actually equivalent, even though it may not seem like that at first sight. ocw.mit.edu
Definition 1.2.9. Let A
be a set. If A is empty, then sup A := ¥. If A is not bounded above, then sup A := ¥. If A is empty, then inf A := ¥. If A is not bounded below, then inf A := ¥. For convenience, ¥ and ¥ are sometimes treated as if they were numbers, except we do not allow arbitrary arithmetic with them. We make R := R [ f ¥;¥g into an ordered set by letting
2.5 Series
Note: 2 lectures A fundamental object in mathematics is that of a series. In fact, when the foundations of analysis were being developed, the motivation was to understand series. Understanding series is important in applications of analysis. For example, solving differential equations often includes series, and differential equations are the basis
1) + j j=0 p(n + 1)(n + 1)
The terms do not go to zero and hence åcn cannot converge. ocw.mit.edu
3.1.2 Limits of functions
If a function f is defined on a set S and c is a cluster point of S, then we define the limit of f (x) as x gets close to c. It is irrelevant for the definition if f is defined at c or not. Furthermore, even if the function is defined at c, the limit of the function as x goes to c can very well be different from f (c). ocw.mit.edu
3.5.2 Infinite limit
Just as for sequences, it is often convenient to distinguish certain divergent sequences, and talk about limits being infinite almost as if the limits existed. ocw.mit.edu
4.1 The derivative
Note: 1 lecture The idea of a derivative is the following. If the graph of a function looks locally like a straight line, then we can then talk about the slope of this line. The slope tells us the rate at which the value of the function is changing at that particular point. Of course, we are leaving out any function that has corners or discontinuit
(a) j0(c) = f 0(c) j(b) j(a) :
The mean value theorem has the distinction of being one of the few theorems commonly cited in court. That is, when police measure the speed of cars by aircraft, or via cameras reading license plates, they measure the time the car takes to go between two points. The mean value theorem then says that the car must have somewhere attained the speed you
5.1 The Riemann integral
Note: 1.5 lectures An integral is a way to “sum” the values of a function. There is often confusion among students of calculus between integral and antiderivative. The integral is (informally) the area under the curve, nothing else. That we can compute an antiderivative using the integral is a nontrivial result we have to prove. In this chapter we
5.1.3 More notation
When f : S R is defined on a larger set S and [a;b] S, we say f is Riemann integrable on [a;b] if the restriction of f to [a;b] is Riemann integrable. In this case, we say f and we write ocw.mit.edu
6.2.1 Continuity of the limit
If we have a sequence of continuous functions, is the limit continuous? Suppose f is the (pointwise) limit of f If lim xk = x we are interested in the following interchange of limits. The equality we have to prove (it is not always true) is marked with a question mark. In fact, the limits f fng. to the left of the question mark might not even exist
6.2.3 Derivative of the limit
While uniform convergence is enough to swap limits with integrals, it is not, however, enough to swap limits with derivatives, unless you also have uniform convergence of the derivatives themselves. ocw.mit.edu
6.3 Picard’s theorem
Note: 1–2 lectures (can be safely skipped) A first semester course in analysis should have a pièce de résistance caliber theorem. We pick a theorem whose proof combines everything we have learned. It is more sophisticated than the fundamental theorem of calculus, the first highlight theorem of this course. The theorem we are talking about is Picard
6.3.3 Examples
Let us look at some examples. The proof of the theorem gives us an explicit way to find an h that works. It does not, however, give us the best h. It is often possible to find a much larger h for which the conclusion of the theorem holds. The proof also gives us the Picard iterates as approximations to the solution. So the proof actually tells us h
Description
Cartesian product of A and B direct image of A by f inverse image of A by f inverse function composition of functions equivalence class of a cardinality of a set A power set of A is equal to y is less than y is less than or equal to y is greater than y is greater than or equal to y supremum of E infimum of E the complex numbers the extended real nu
R[a;b]
b Z b , f (x) dx a ln(x), log(x) exp(x), ex xy f ku Rn C(S;R) diam(S) ocw.mit.edu
Description
continuously differentiable functions f : S R open ball in a metric space closed ball in a metric space closure of A interior of A boundary of A ocw.mit.edu
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Analyse. Anleitungen und Regelsysteme für qualitativ Forschende. 8. Auflage. 5. So gelingen Ihre Interviews. 9. Mögliche Probleme. 15. Transkription. |
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