“슬기로운 어바나-샴페인 생활 101” 은 제가 초기 정착 때 경험한 것들을 시간별로 정리해서 새롭게 오시는 분들에게 필요한 정보를 공유하는 것을 목적으로 하는 프로젝트 입니다. 목차1. 한국에서 어바나-샴페인 (Urbana-Champaign) 가는 방법2. 어바나-샴페인에서 집 구하기 가이드3. 일리노이 주 운전면허 필기시험 기출문제 한국어 번역: 이것만 보고 가시면 무조건 필기 합격!!4. 일리노이주 운전면허 신청 방법5. UIUC 학생증/교직원 카드 신청하기6. 은행계좌 개설하기7. 의료보험 가입하기8. 대중교통 (버스) 이용하기9. 학교 식당 (Dining hall) 10. 한식재료 구매하기###S1. 세금 환급 (Tax Refund) 받기 (feat. 세금환급 대행 회사 추천)S2. 어바나-샴페인…
There is a corn experimental field as shown below. While regular corn farmers typically sow the entire field at once without dividing it into plots, researchers divide the field into plots and differentiate treatments to derive experimental results. The yield data obtained from field experiments should be in the common unit used by farmers, which is Mg/ha or bu/acre. However, our experimental field is not as large as a hectare (ha). Even if a certain experimental field is as large…
외국은 그렇지 않은 거 같은데 한국은 저널의 SCI(E) 등재 여부, Impact Factor 를 무척이나 따지는 것 같습니다. 과거 가졌던 편견 중 하나는 한국이 뭔가 보수적이어서 논문 내용의 퀄리티가 아닌, 이런 뒤쳐져 보이는 지표를 따지는가 싶었지만, 예전에 Predatory journals 에 한번 우연히 들어가서 내용을 보다가 형편없는 중학생 리포트 숙제 같은 것도 연구 논문으로 출판될 수 있다는 것에 놀랐고, 또 그 저널에 한국 사람이 그렇게 많은 것에 또 놀랐습니다. 아마 이런 논문에 대한 스크린 작업의 일환으로 그런 평가 기준을 둔 것이 아닐까…
데이터의 정규화는 여러 가지 주요 이유로 데이터를 시각화 할 때 필요한데, 가장 중요한 이유는 척도의 균일성 (scale uniformity) 때문입니다. 서로 다른 데이터 변수들은 크게 다른 척도와 단위를 가질 수 있습니다. 예를 들어, 곡물 수확량은 Mg/ha 일 수 있고, 영양소 함량은 일반적으로 % 범위 내에 있을 수 있습니다. 이러한 데이터를 정규화 하면 단위가 다른 여러 개의 변수를 동일한 그래프에서 비교하고 시각화 할 수 있습니다. 또한, 정규화는 데이터의 해석 능력 (visualization interpretability) 을 향상시킵니다. 정규화된 데이터는 패턴에 대한 해석을 더 쉽게 할…
I have 1,000 data points of measurements of the length (mm) and weight (mg) of wheat grains. With this data, I want to analyze the relationship between the length and weight of the wheat grain to propose an equation model that can predict grain weight. I will draw a graph to visualize the data. If you are new to R, you can copy and paste the following code into your R script window to obtain the same graph as shown…
Previously, I scanned wheat grains to obtain the area of each grain, and then measured the weight of each grain corresponding to its area in order to develop a model equation. The following regression demonstrates the relationship between grain area and weight. # Data download https://www.kaggle.com/datasets/agronomy4future/wheat-grain-area-vs-weight I obtained the equation y = 3.3333x – 13.7155, where y is the grain weight (mg) and x is the grain area (mm2), using both Excel and R. However, this model predicts negative values…
A factorial experiment involves the simultaneous manipulation of multiple factors or independent variables (x) to study their effects on a dependent variable (y). The experiment is called factorial because it involves testing multiple factors simultaneously. In factorial experiments, the combination of the different levels of each factor being tested is called a factorial, and each factorial represents a unique combination of these levels. For instance, N0_Genotyp1, N0_Genotyp2, N1_Genotyp1, N1_Genotyp2, etc. are different factorials used to conduct the experiment and analyze…
This is my experimental data. There are 10 corn varieties, and I want to analyze the effect of nitrogen treatments (N0, N1) on grain yield for each variety. This is One-Way ANOVA analysis. Let’s assume that there are no blocks for the replicates. Therefore, the statistical model will be a One-Way ANOVA with no blocks. If we run the above analysis, we can observe the overall effect of nitrogen treatments on grain yield across all varieties, as they are pooled…
One of the problems that can occur when drawing graphs using R is that the x-axis of the graph is sorted alphabetically. There is data as shown above. I used this data to create a graph as shown below. The above graph displays Amonium Sulfate first according to alphabetical order. However, I want to show the treatments in the following order: Calcium Nitrate first, followed by Urea, then Sodium Nitrate, and lastly Ammonium Sulfate. Here are two ways to change…
I’ll now show you how to change the order of variables in a graph. For this example, I have prepared some data and will create a graph using it. Now, let’s re-order the variables so that Calcium Nitrate comes first, followed by Urea, then Sodium Nitrate, and lastly Ammonium Sulfate. First, let’s take a look at the variables: The variables in R are currently ordered alphabetically by default. The following code will change the order of the variables as desired:…
If you need to change the text of a specific column while analyzing data in R, I will introduce how to do it. First, let’s create a simple dataset First, let’s rename the column names. We will change the ‘Nation’ column name to ‘Country’ and the ‘Sex’ column name to ‘Gender’. If you enter the following code, the column names will be updated accordingly. If the nationality of DAVID is Canada instead of Germany, you can update by entering the…
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I have the following data. Nitrogen Sulphur Rep Yield 0 0 1 1.0 0 0 2 0.9 0 0 3 0.8 N1 S1 1 1.0 N1 S1 2 1.2 N1 S1 3 1.3 N1 S2 1 2.1 N1 S2 2 2.2 N1 S2 3 2.3 N2 S1 1 1.4 N2 S1 2 1.6 N2 S1 3 1.7 N2 S2 1 2.5 N2 S2 2 2.6 N2 S2 3 2.8 Let’s assume that this data is the result of investigating how…
Sometimes, I see many people managing their data as columns like the example below. It seems convenient because we can see our data all at once. However, this data format is problematic for data analysis, which fundamentally relies on variables, namely independent and dependent variables. Download data file (.csv) https://github.com/agronomy4future/raw_data_practice/blob/main/yield_per_location.csv In the given data format, each level for the independent variable (i.e., location) was not combined in one column, and therefore we need to rearrange the data format. If the…
In this session, I will introduce the method of calculating the Best Linear Unbiased Estimator (BLUE). Instead of simply listing formulas as many websites do to explain BLUE, this post aims to help readers understand the process of calculating BLUE with an actual dataset using R. I have the following data. location sulphur (kg/ha) block yield Cordoba 0 1 750 Cordoba 24 1 1250 Cordoba 36 1 1550 Cordoba 48 1 1120 Cordoba 0 2 780 Cordoba 24 2 1280…
When we draw regression lines for a group, they are usually of the same type, such as simple linear regression. Here is an example using yield data for different nitrogen rates per genotype. Then, the regression graph for each group would be shown below. I think it would be better to show the quadratic regression line for genotype A. In this case, how can we create separate linear and quadratic regression graphs for each group in the same panel? Data…
1. Unisexual flower a flower that has either male or female reproductive structures, but not both. Unisexuality can be divided into two categories. 1-1) Monoecious: a type of plant that has separate male and female flowers on the same plant. The representative plants of monoecious plants are corn and other Cucurbitaceae crops such as squash, cucumber, watermelon, pumpkin, etc. The corn we eat is actually the female flower of the corn plant. It is fertilized by the pollen from the…
Before Getting Started!! This content applies only to bisexual flowers. If it is not a bisexual flower, there is no reason to use cytoplasmic male sterility for seed production. It is recommended to read the post below first. □ Sexual Classification of Plants ■ Male Sterility: the condition in which plants are unable to produce functional pollen grains or male gametes, which is necessary for sexual reproduction. ■ Male Fertility: the ability of male reproductive structures (stamens) to produce viable…
To gain a basic understanding of the topic, I recommend reading the following posts. Analysis of Covariance (ANCOVA) I have a dataset as shown below, and I would like to analyze crop yield, and height based on different fertilizer types (Control, Slow-release, and Fast-release). The experimental design is a Completely Randomized Design (CRD) with 10 replicates. Rep Fertilizer Yield Height Fertilizer Yield Height Fertilizer Yield Height 1 Control 12.2 45.0 Slow 16.6 63.0 Fast 9.5 52.0 2 Control 12.4 52.0…
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…
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…