출결 및 과제 점검표

학번 : 21207221

이름 : 남연숙

주	출석	지각	결석	과제	비고
1주(9/1)	○				수강정정기간
2주(9/8)					추석연휴
3주(9/15)	○
4주(9/22)	○
5주(9/29)	○
6주(10/6)	○
7주(10/13)	○
8주(10/20)	○				중간고사
9주(10/27)	○
10주(11/3)			○		감기몸살
11주(11/10)	○
12주(11/17)					휴강
13주(11/24)	○
14주(12/1)	○
15주(12/8) 보강	○
16주(12/15)	○			과제 ○	기말고사
계	13		1	1

<각 주별 강의요약 첨부>

1주차

Orientation

2주차

Consecutive holidays of Chuseok

3주차

In this class, you can on conclusion the Policy Analytics that create the future is to leverage the resources of the past.

And we learn the first process to achieve the goals policy  is in reality, grasping the correct problem.

Professor said, when you want to learn a foreign langauage, the best way is live with foreigner.

To getting your job, He recommend internship that you experience real society and get useful technique.

4주차

In this class, We learn about various model type.

Even though model type is various, all have one goal setting.

and professor add Universal Students must study at least 8 hours.

The Statics used many areas, for example Economics , There are Engineering, Sports, Business.

These Statistics devide Inferential Statistics and Descriptive Statistics.

5주차

Professor explain to describe of data.

And we learn a various method of express our data presentation.

I'm very impression stem-and-leaf displaly.

because it's very simple to find many data.

And we are practice to use "Stata system" that we are summarize easier than past.

In conclusion, I found by this class, that data presentation was devide qualitative data and numerical data.

6주차

The professor explain concepts of  matrix and probability simply.

Then, we learn about probability which is categorized experiment and outcomes.

Outcomes included sample point that means most basic outcome of an experiment, and sample space that means collection of all possible outcomes.

Events mean any collection of sample points , and it is divided simple event, compound event.

Sample space is described by venn diagram, contingency table, decision tree diagram.

And we learned compound events (that included intersection and union), probabilities.

I already learned about this part by my high school education process so this part very friendly to me.

7주차

Statistical methods categorized descriptive statistics and Inferential Statics.

Inferential Statistics involves estimation and hypothesis testing , it has purpose that make decisions about population characteristics.

Estimators theoretical basis is sampling distribution that results from drawing all possible and samples of a fixed size.

And we learn about sampling from normal populations and non-normal populations which has more imbalance population distribution.

As sample size gets large enough (which is non-normal populations.), sampling distribution becomes almost normal.

And we practice stata program about hypotheses, i think this practice most difficult in our class.

8주차

Midterm-exam

9주차

The Hypothesis Testing is Inferential statistics which is statistical methods.

Null hypothesis is has serious outcome if incorrect decision made and always has equality sign.

Alternative Hypothesis is opposite of null hypothesis so always has inequality sign.

And we think about Hypotheses ,include alternative hypothesis and null hypothesis, of 4 example.

The last part is decision making risks , so we must know errors in making decision.

Type one error is reject true null hypothesis and type two error is do not reject false null hypothesis.

10주차

Absent because of cold did.

11주차

Today topic is city planning theory and Types of probabilities models.

First, synoptic rationalism is idealism that set a goal in advance and we run for this goal.

The disjointed instrumentalism was opposition to synoptic rationalism which argue rational choice was unreal.

The choice theory argued city planning process is choice process for future acting.

The advocacy and pluralism  defend the citizen's rights which example is NIMBY, PIMFY.

Advocacy theory has experience to success through citizen's democratic participation.

After break time, we learn about types of probabilities models which categorized regression models and correlation models and other models.

Then we practice to estimate for simple linear regression model  by using stata program.

12주차

No classes because of the professor business trip.

13주차

Let's notice about the paired-sample t Teset for mean difference.

First,  tests means of 2 related populations.(paire or matched, repeated measures)

Second, eliminates variattion among subjects.

The assumptions about this paired-sample t test is  both population are normally distributed.

If not normal, can be approximated by normal distribution.

The Z test for difference in two proportions assumptions is populations are independent.

and populations follow binomial distribution and normal approximation can be used.

14주차

Today's part is simple linear regression.

First, the models are representation of some phenomenon.

and mathematical model is a mathematical expression of some phenomenon.

The regression models are one of the kind of probabilistic models.

This models are answer 'what is the relation ship between the variables?'

We can expressed regression models by using population & sample example.

If you imagine you have some population which has unknown relationship.

Then you can random sample in the population.

When you applied regression function to random sample, this is also included population

15주차

This class is our last class.

Today part is hypothesizing the deterministic component.

The regression modeling steps is categorized 5 steps.

And we can estimate unknown model parameters and specify and evaluate model.

The last step is use model for prediction & estimation.

We can noticed population multiple regression model by using modeling example.

16주차

A final exam.