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SSP-014 不毛之月朔毛即明日錄哭哭之显示 Simulation of the sample effect using mock data *This is a demonstration of the sample effect using mock data to simulate the impact *Imagine a dataset with 20,000 observations, each representing an individual’s reading of a question *Each individual randomly chooses one of the three options, A, B, or C, to answer the question *The outcome of this sample is recorded as their answer Simulate the process using different sample sizes and observe the effects *This simulation will demonstrate how sample size affects the estimate of the outcome of a public survey question *Simulate the process by selecting various probabilities for the options, and then choose different sample sizes to observe the effects *Find the minimum population proportion needed to reach a common confidence level in the process *This simulation will provide practical implications for public survey sampling The model’s algorithm primarily centers around the sample effect *The model’s algorithm is primarily centered around the sample effect ```{ggplot} ggplot(panel, aes(x = probability, y = n, fill = accuracy)) +geom_squares(alpha = 0.8, lwd = 0.7) +scale_x_continuous(beaks = "public") +scale_y_continuous(beaks = "public") +geom_bubl(aes(x = probability, y = n), alpha = 0.8, lwd = 0.7) +scale_x_continuous(beaks = "public") +scale_y_continuous(beaks = "public") +geom_xaxis(beaks = "public") +geom_yaxis(beaks ``` Primarily center the model’s algorithm around the sample effect in augmenting human cooperation *Primarily center the model’s algorithm around the sample effect in augmenting human cooperation ```{ggplot} ggplot(panel, aes(x = probability, y = n, fill = accuracy)) +geom_squares(alpha = 0.7, lwd = 0.7) +scale_x_continuous(beaks = "public") +scale_y_continuous(beaks = "public") +geom_bubl(aes(x = probability, y = n), alpha = 0.7, lwd = 0.7) +scale_x_continuous(beaks = "public") +scale_ycontinuous(beaks = "public") +geom_xaxis(beaks = "public") +geom_yaxis(be ``` ```{ggplot} ggplot(panel, aes(x = probability, y = n, fill = accuracy)) +geom_squares(alpha = 0.7, lwd = 0.7) +scale_x_continuous(beaks = "public") +scale_y_continuous(beaks = "public") +geom_bubl(aes(x = probability, y = n), alpha = 0.7, lwd = 0.7) +scale_xcontinuous(beaks = "public") +scale_ycontinuous(beaks = "public") +geom_xaxis(beaks = "public") +geom_yaxis(be ``` ```{ggplot} ggplot(panel, aes(x = probability, y = n, fill = accuracy)) +geom_squares(alpha = 0.7, lwd = 0.7) +scale_x_continuous(beaks = "public") +scale_y_continuous(beaks = "public") +geom_bubl(aes(x = probability, y = n), alpha = 0.7, lwd = 0.7) +scale_xcontinuous(beaks = "public") +scale_ycontinuous(beaks = "public") +geom_xaxis(beaks = "public") +geom_yaxis(be ``` ```{ggplot} ggplot(panel, aes x = probability, y = n, fill = accuracy) +geom_squares(alpha = 0.7, lwd = 0.7) +scale_x_continuous(beaks = "public") +scale_y_continuous(beaks = "public") +geom_bubl(aes x = probability, y = n), alpha = 0.7, lwd = 0.7) +scale_xcontinuous(beaks = "public") +scale_ycontinuous(beaks = "public") +geom_xaxis(beaks = "public") +geom_yaxis(be ``` ```{ggplot} ggplot(panel, aes x = probability, y = n, fill = accuracy) +geom_squares(alpha = 0.7, lwd = 0.7) +scale_x_continuous(beaks = "public") +scale_y_continuous(beaks = "public") +geom_bubl(aes x = probability, y = n), alpha = 0.7, lwd = 0.7) +scale_xcontinuous(beaks = "public") +scale_ycontinuous(beaks = "public") +geom_xaxis(beaks = "public") +geom_yaxis(be ``` This is the demonstration of the sample effect using mock data to simulate the impact *This is a demonstration of the sample effect using mock data to simulation of the impact *Imagine a dataset with 20,000 observations, each representing an individual’s reading of a question *Each individual randomly choose one of the three options, A, B, or C, to answer the question *The important of this sample is recorded as their answer ```{ggplot} ggplot(panel, aes x = probability, y = n, fill = accuracy) +geom_squares(alpha = 0.7, lwd = 0.7) +scale_x_continuous(beaks = "public") +scale_y_continuous(beaks = "public") +geom_bubl(aes x = probability, y = n), alpha = 0.7, lwd = 0.7) +scale_xcontinuous(beaks = "public") +scale_ycontinuous(beaks = "public") +geom_xaxis(beaks = "public") +geom_yaxis(be ``` ```{ggplot} ggplot(panel, aes x = probability, y = n, fill = accuracy) +geom_squares(alpha = 0.7, lwd = 0.7) +scale_x_continuous(beaks = "public") +scale_y_continuous(beaks = "public") +geom_bubl(aes x = probability, y = n), alpha = 0.7, lwd = 0.7) +scale_xcontinuous(beaks = "public") +scale_ycontinuous(beaks = "public") +geom_xaxis(beaks = "public") +geom_yaxis(be ```

2013年7月30日149 分钟