캐나다 워크퍼밋을 신청하고 최종 워크퍼밋 비자를 받기까지 넉달이 걸린 반면 미국 J1 비자 신청을 위한 DS-2019 를 받는 것에는 3주가 걸렸습니다. 학교측에서 DS-2019 서류를 처리해 주는 것을 보면서 미국이 참 전산화가 잘 되어 있다는 생각을 했습니다. DS-2019 서류를 받은 뒤 J1 비자를 수령 받는 방법을 정리해 보았습니다. 1) DS-2019 서류 수령 미국 대학 측으로 부터 DS-2019 서류를 수령 받았습니다. 저는 현재 캐나다에서 일하고 있지만 제 국적이 대한민국 이여서 J1 비자 인터뷰는 캐나다에서 할수는 없고 주한 미국 대사관에서 해야 한다고 합니다….
In this session, using Python, I will draw a normal distribution graph using the actual data I collected. I measured individual grain areas for two wheat genotypes. For Cultivar_A, I measured the area for 1,225 grains and for Cultivar_B, I measured the area for 1,841 grains. Therefore, the total number of grain area data is 3,066. This is natural data collected by me in the actual cultivation field, and it would be interesting to see if it also follows a…
Today, I will explain the meaning of the F-value in testing for significance through statistical processing. Let me give you an example. Suppose we want to determine whether there are differences in the yield according to the varieties (A, B, C). The total experimental unit is 12 (3 varieties x 4 replicates). What would happen if there is a significant difference in yield among varieties A and C? If there is a large difference in yield between these varieties, the…
Sometimes, when creating graphs using R, there may be a need to include superscripts or subscripts in axis text or titles. In this post, I will introduce about how to enter text with superscripts or subscripts. I will generate one simple data and draw a graph to demonstrate. Here, I want to add superscripts or subscripts to the axis titles of the graph. For example, for the x-axis, I want to name it as “GenotypeTM” and for the y-axis, I…
Here is data for x and y. I would like to perform regression analysis to understand how y changes with x. n x y 1 10 30 2 20 40 3 30 50 4 40 80 5 50 90 6 60 100 7 70 120 I have data for x and y as described above, and want to determine the regression model for this data, where the dependent variable y changes according to the independent variable x, in the form…
Logistic regression is a type of statistical analysis used to model the relationship between a binary (yes/no) dependent variable and independent variables. The goal of logistic regression is to find a relationship between the independent variables (x) and the probability of a particular outcome for the dependent variable (y). The logistic regression model calculates the probability of a certain outcome by applying a logistic function to the linear combination of the independent variables. Here is one example. Sulphur improves plant…
When we make graphs, the unit is great and the number would be overlapped. Here is an example. Now, I’d like to change the unit of number. For example, I want to divide each value by 1000, so that to show 5 to 30 in x-axis. We can add below codes.
In my previous post, I explained what split-plot design and the statistical model is, and also how it is different RCBD. What is split-plot design in agronomy research? I explained the main difference between split-plot design and RCBD is that in split-plot design, error is divided into two (error a and b), increasing the significance of interaction between the main plot and sub-plot. Now our interest lies in cases where we have three factors. In a split-plot design, we typically…
Split-plot design has been widely used particularly in the agronomy research. In split-plot design, the experimental units are divided into smaller units. Split-plot designs are useful when some factors are difficult or expensive to change or when the levels of the factors cannot be randomized (I’ll explain in detail later). Split-plot design consists of one whole plot and one subplot. The whole plot factor is randomly assigned to the experimental units, while the subplot factor is applied to a smaller…
Google Colaboratory (aka. Colab) is a cloud-based platform that provides a Jupyter notebook environment and therefore users can write and run Python code. You don’t have to install Anaconda to use Jupyter notebook. If you have a google account, simply you can analyze data. Google Colab is a powerful tool for collaborative coding and data analysis, providing users with an easy-to-use platform with a wide range of features and resource. I introduce how to set up Google Colab. Step 1)…
Sample No. x y 1 10 30 2 20 40 3 30 50 4 40 80 5 50 90 6 60 100 7 70 120 Here is a dataset that allows us to analyze the relationship between x and y and obtain the model equation, y= β0 + β1x. Although statistical programs can provide us with results in just 10 seconds, it is more important to understand the principles behind the calculations than to simply know how to run the…
When you conduct statistical analysis, you might want to include/exclude some variables. For example, here is one data. This is data about how yield, grain number (GN) and averge grain weight (AGW) are different according to two different fertilizers (N0, N1) in five genotypes (CV1 – CV5). That is, there will be 10 treatments [Genotype (5) x Nitrogen (2) =10]. Replicates are 10 as blocks, and therefore experimental unit will be 30 [10 treatments x 3 blocks = 30]. What…
Odds and logit is the basic concept to understand logistic regression. Today I’ll explain what it is as much as easily. Do you know a comic book, ‘Slam Dunk’? I’ll explain odds with this story. 1) Odds Now, Shohoku high school is playing games with other high schools in the tournament. In the first round, Shohoku high school won 4 games and lost 6 games out of 10 games. Now the winning odds of Shohoku high school is 4/6 ≈…
I wrote many codes in R and now I want to delete all of them. You can click the broom icon to delete all. But, you can use this code to delete all.
Previous post□ How to analyze linear plateau model in R Studio? In my previous post, I explained how to analyze linear plateau model. I simulated yield data for five different crop varieties with different sulphur applications, and suggsted the optimum sulphur application would be 23.3 kg/ha based on the linear plateau model. In this time, I’ll explain how to analyze quadratic plateau model with the same data using R studio 1) Data upload If you run the below code, the…
When we talk about regression, it’s usually about simple linear regression model. This is about the relationship between two variables. FYI□ Simple linear regression (1/5)- correlation and covariance□ Simple linear regression (2/5)- slope and intercept of linear regression model Linear plateau model is similar with simple linear model, but linear plateau model is a segmented model, and this statistical model is interested in the critical value (the x-value above which there is no further increase in y), indicating the plateau value (the statistically highest value…
사무실 동료가 미국 대학 교수 면접 인터뷰가 있다고 해서 잠깐 사무실을 비워 줬습니다. 그래서 사무실 맞은편에 있는 University Center 건물에 가 봤습니다. University Center 는 궬프대학교에서 여러가지 편의시설이 있는 곳입니다. 학교 식당과 안경점, 치과, 약국, 프린트 샵 등 학생들을 위한 여러가지 편의 시절이 이곳 1층에 위치하고 있습니다. 30분 정도 시간을 보낼 곳이 필요해서 University Center 를 층별로 한번 둘러보기로 했습니다. 4층을 가 봤더니 궬프 대학교의 역사에 대해 여러가지 정보를 볼수 있었습니다. 게시판을 둘러보던 중 Korea 단어가 보여서 뭔가 해서 자세히…
Here is one data. P-values are summarized for genotypes at difference fields. Now I’d like to add symbols; *,**,*** and n.s. If p-value is less than 0.05, it will be *, and if p-value is less than 0.01, it will be **, and if p-value is less than 0.001, it will be ***, and if all conditions are not met, it will be n.s. So, I’ll add this code in D column in the excel, and drag this code to…
Simple Linear Regression Series 1) Simple linear regression (1/5)- correlation and covariance 2) Simple linear regression (2/5)- slope and intercept of linear regression model 3) Simple linear regression (3/5)- standard error of slope and intercept 4) Simple linear regression (4/5)- t value on the slope and intercept 5) Simple linear regression (5/5)- Coefficient of determination In my previous post, I explained how to calculate standard error of slope and intercept in simple linear regression model. Now, I’ll explain how to calculate t…
1월말에 온타리오 지역에 폭설이 내렸습니다. 사무실에서 일을 하다가 잠깐 리프레쉬 할겸 오랜만에 캠퍼스를 한번 둘러 봤습니다. 사무실에서 보이는 캠퍼스의 설경이 무척이나 예뻐 보입니다. 빌딩 밖을 나와서 도서관 쪽으로 이동해 보기로 했습니다. 양 옆에 가로수가 눈에 쌓여 있는 모습이 무척이나 이쁜 설경 모습입니다. 학교 메인 건물인 Johnston Hall 입니다. 유럽 건물 느낌이 나는 이곳은 학생 기숙사 입니다. 그리고 캠퍼스 이곳 저곳을 둘러 보았습니다. 4월말까지는 이런 겨울 풍경이 계속 된다고 합니다. 처음 캐나다 오기전 겨울밀을 10월에 파종하고 stem elongation (GS30) 이 4월…
In my previous post, I explained how to add extra column and row to calculate mean respectively. In R, how to add extra column and row to calculate mean respectively? Now, I’d like to substrtact the mean from each value in each column. This will be genotypic effect.
Let’s generate one data table. Now, I’d like to calculate mean of each column and row. For example, I want to calculate mean of ENV1 to ENV5, and also CV1 to CV5. First, I’ll calculate mean of each row (ENV1 to ENV 5). I discarded Environment row (dataA %>% select(-Environment)) because it’s not a numeric. Now, I’ll calculate mean of each column (CV1 to CV5). Now, mean of each column and row was calculated.
GxE interaction is when the phenotypic difference between a pair of genotypes is larger or smaller in one environment than in another environment. It is important to understand that what genotypes have different phenotypic values in two environments is not the same as GxE interaction. Please look at above graph. Both genotypes had a different phenotype in the two different environments (Env1 and Env2), but there was no interaction in this case because the difference between the phenotypic values was…
MandalArt chart became famous due to Shohei Ohtani who is a baseball player in MLB. This method is to pinpoint eight specific ways about one major goal. News articleHow Shohei Ohtani Visualized His Baseball Success As a crop physiologist, I set up my own MandalArt chart to visually organize and explore the interconnected aspects of crop physiology. © 2022 – 2023 https://agronomy4future.com
Previous post!!□ Simple linear regression (1/5)- correlation and covariance□ Simple linear regression (2/5)- slope and intercept of linear regression model In my previous post, I explained how to calculate slope (β1) and intercept (β0) of linear regression model. If you well followed my previous posts, you will get the above result, y= 89.0 + 1.5x Now our interest is how to calculate standard error in the intercept and slope (Red box). Here is the equation to obtain standard error of…
□ Simple linear regression (1/5)- correlation and covariance In my previous post, I explained about correlation and covariance. Now, I’ll explain about slope (β1) and intercept (β0) of linear regression model. In the whole picture to explain a linear regression model, β1 is calculated as β1 = r * Sy / Sx We already know how to calculate correlation (r), and only we need to calculate the ratio between standard deviation of x and y. Let’s go back to the…
Since today, I’ll explain simple linear regression model. There are lots of information about linear regression on websites, but I believe I’ll tell you about what most people don’t mention. My philosophy on data analysis and statistics is to fully understand the concept, not simply follow what software programs say. Therefore I usually calculate statistical concepts by hand, and only my hand calculation is exactly same as the software programs provide, I say I understand the concept. In this context,…
geom_hline(data=data.frame(variety=c(“A”, “B”)), aes(yintercept=c(195.4028, 206.0819)), linetype=”dashed”, color=”Dark blue”) +
When we analyze data, we may need to show graphs depicting normal distributions. These graphs differ from density graphs as they convey various concepts that simple bar graphs cannot. While it is easy to draw these graphs in Excel, understanding the underlying concepts is crucial. In this article, I will explain what the Probability Density Function (PDF) is, and I will show how we can calculate it in both Excel and R. Here is a dataset of 1,000 individual wheat…