Tech Journal

As you’ve learned, strings are a crucial class of data because they represent textual information. Data professionals encounter strings all the time, so it’s important to become familiar with different ways of manipulating and working with them. This reading will review the string formatting techniques you’ve learne... Read More

목차 제1절 통계학 개론 제2절 기초 통계 분석 t-검정 분산분석(ANOVA) 제3절 다변량 분석 제4절 시계열 예측 제5절 주성분 분석 1. t-검정(t-test) 일 표본 t-검정(one-sample t-test) 일(단일) 표본 t-검정은 하나의 표본이 어떤 기준값(모집단)과 통계쩍으로 유의한 차이가 있는지 평가하는 가설 검정 방법입니다. 이 검정은 모집단의 분산(또는 표준편차)을 알수 없고, 표본 데이터를 통해 모평균을 추청해야 할 때 사용됩니다. 일 표본 단측 t-검정(one-sample o... Read More

Activity: Work with strings in Python Introduction Data professionals work with a lot of string data. For example, while analyzing the results of a marketing campaign, you may need to review item descriptions or customer names, which is stored as string data. Becoming comfortable working with strings in Python is ... Read More

As you know, strings are an important class of data because they represent text. Data professionals encounter strings all the time, so it’s important to become familiar with different ways of manipulating and working with them. This reading will review the string formatting techniques you’ve learned and also introdu... Read More

You’ve learned about for loops in Python and have explored some examples. For loops are like while loops, but instead of looping continuously until a condition is met, for loops iterate over each element of an iterable sequence, allowing you to perform an action or evaluation with each iteration. This is an importan... Read More