Step 3: Preview the data
view(TAS_original_data_new)
head(TAS_original_data_new)
## # A tibble: 6 × 101
## TAS TAS05 TAS09 TAS15 ER30001 ER30002 ER32000 ER32006 ER33801 ER33802
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 NA 1 NA 4 37 1 2 1288 3
## 2 1 NA 1 NA 4 38 2 2 6880 2
## 3 2 NA 1 1 4 39 2 2 289 3
## 4 1 NA NA 1 4 41 2 2 1157 3
## 5 2 1 1 NA 4 180 2 3 771 2
## 6 2 1 1 NA 5 32 2 2 624 3
## # ℹ 91 more variables: ER33803 <dbl>, TA050001 <dbl>, TA050044 <dbl>,
## # TA050047 <dbl>, TA050050 <dbl>, TA050065 <dbl>, TA050066 <dbl>,
## # TA050067 <dbl>, TA050070 <dbl>, TA050071 <dbl>, TA050127 <dbl>,
## # TA050128 <dbl>, TA050129 <dbl>, TA050130 <dbl>, TA050573 <dbl>,
## # TA050574 <dbl>, TA050575 <dbl>, TA050594 <dbl>, TA050595 <dbl>,
## # TA050639 <dbl>, TA050663 <dbl>, TA050664 <dbl>, TA050665 <dbl>,
## # TA050670 <dbl>, TA050675 <dbl>, TA050676 <dbl>, TA050884 <dbl>, …
2005
Mean
Mean_B5A <- TAS_original_data_new %>% select(TA050044) %>% drop_na() %>% summarize("Responsibility_for_self" = mean(TA050044))
Mean_B5D <- TAS_original_data_new %>% select(TA050047) %>% drop_na() %>% summarize("Managing_own_money" = mean(TA050047))
Mean_B6C <- TAS_original_data_new %>% select(TA050050) %>% drop_na() %>% summarize("Money_management_skills" = mean(TA050050))
Mean_C2D <- TAS_original_data_new %>% select(TA050065) %>% drop_na() %>% summarize("Worry_about_expenses" = mean(TA050065))
Mean_C2E <- TAS_original_data_new %>% select(TA050066) %>% drop_na() %>% summarize("Worry_about_future_job" = mean(TA050066))
Mean_C2F <- TAS_original_data_new %>% select(TA050067) %>% drop_na() %>% filter(TA050067 <= 7) %>% summarize("Discouraged_about_future" = mean(TA050067))
Mean_G1 <- TAS_original_data_new %>% select(TA050573) %>% drop_na() %>% filter(TA050573 < 3) %>% summarize("Education_status" = mean(TA050573))
Mean_G2 <- TAS_original_data_new %>% select(TA050575) %>% drop_na() %>% filter(TA050575 > 0) %>% summarize("High_school_graduation_year" = mean(TA050575))
Mean_G30A <- TAS_original_data_new %>% select(TA050639) %>% drop_na() %>% filter(TA050639 > 0) %>% summarize("Likelihood_of_well-paying_job" = mean(TA050639))
Mean_G41A <- TAS_original_data_new %>% select(TA050663) %>% drop_na() %>% summarize("Importance_of_job_status" = mean(TA050663))
Mean_G41B <- TAS_original_data_new %>% select(TA050664) %>% drop_na() %>% summarize("Importance_of_decision-making" = mean(TA050664))
Mean_G41C <- TAS_original_data_new %>% select(TA050665) %>% drop_na() %>% summarize("Importance_of_challenging_work" = mean(TA050665))
Mean_G41H <- TAS_original_data_new %>% select(TA050670) %>% drop_na() %>% summarize("Importance_of_healthcare_benefits" = mean(TA050670))
Mean_G41P <- TAS_original_data_new %>% select(TA050675) %>% drop_na() %>% filter(TA050675 < 8) %>% summarize("Importance_of_job_central_to_identity" = mean(TA050675))
Mean_H1 <- TAS_original_data_new %>% select(TA050676) %>% drop_na() %>% filter(TA050676 < 8) %>% summarize("General_health" = mean(TA050676))
TAS_descriptive_table <- data.frame(Name = c("Mean_2005"), Mean_B5A, Mean_B5D, Mean_B6C, Mean_C2D, Mean_C2E, Mean_C2F, Mean_G1, Mean_G2, Mean_G30A, Mean_G41A, Mean_G41B, Mean_G41C, Mean_G41H, Mean_G41P, Mean_H1)
2005
Standard Deviation
sd_B5A <- TAS_original_data_new %>% select(TA050044) %>% drop_na() %>% summarize(sd_B5A = sd(TA050044))
sd_B5D <- TAS_original_data_new %>% select(TA050047) %>% drop_na() %>% summarize(sd_B5D = sd(TA050047))
sd_B6C <- TAS_original_data_new %>% select(TA050050) %>% drop_na() %>% summarize(sd_B6C = sd(TA050050))
sd_C2D <- TAS_original_data_new %>% select(TA050065) %>% drop_na() %>% summarize(sd_C2D = sd(TA050065))
sd_C2E <- TAS_original_data_new %>% select(TA050066) %>% drop_na() %>% summarize(sd_C2E = sd(TA050066))
sd_C2F <- TAS_original_data_new %>% select(TA050067) %>% drop_na() %>% filter(TA050067 <= 7) %>% summarize(sd_C2F = sd(TA050067))
sd_G1 <- TAS_original_data_new %>% select(TA050573) %>% drop_na() %>% filter(TA050573 < 3) %>% summarize(sd_G1 = sd(TA050573))
sd_G2 <- TAS_original_data_new %>% select(TA050575) %>% drop_na() %>% filter(TA050575 > 0) %>% summarize(sd_G2 = sd(TA050575))
sd_G30A <- TAS_original_data_new %>% select(TA050639) %>% drop_na() %>% filter(TA050639 > 0) %>% summarize(sd_G30A = sd(TA050639))
sd_G41A <- TAS_original_data_new %>% select(TA050663) %>% drop_na() %>% summarize(sd_G41A = sd(TA050663))
sd_G41B <- TAS_original_data_new %>% select(TA050664) %>% drop_na() %>% summarize(sd_G41B = sd(TA050664))
sd_G41C <- TAS_original_data_new %>% select(TA050665) %>% drop_na() %>% summarize(sd_G41C = sd(TA050665))
sd_G41H <- TAS_original_data_new %>% select(TA050670) %>% drop_na() %>% summarize(sd_G41H = sd(TA050670))
sd_G41P <- TAS_original_data_new %>% select(TA050675) %>% drop_na() %>% filter(TA050675 < 8) %>% summarize(sd_G41P = sd(TA050675))
sd_H1 <- TAS_original_data_new %>% select(TA050676) %>% drop_na() %>% filter(TA050676 < 8) %>% summarize(sd_H1 = sd(TA050676))
new_sd <- data.frame(Name = c("SD_2005"), sd_B5A, sd_B5D, sd_B6C, sd_C2D, sd_C2E, sd_C2F, sd_G1, sd_G2, sd_G30A, sd_G41A, sd_G41B, sd_G41C, sd_G41H, sd_G41P, sd_H1)
TAS_descriptive_table[nrow(TAS_descriptive_table) + 1,] <- new_sd
2005
Range
range_B5A <- TAS_original_data_new %>% select(TA050044) %>% drop_na() %>% summarize("Responsibility_for_self" = range(TA050044))
range_B5D <- TAS_original_data_new %>% select(TA050047) %>% drop_na() %>% summarize("Managing_own_money" = range(TA050047))
range_B6C <- TAS_original_data_new %>% select(TA050050) %>% drop_na() %>% summarize("Money_management_skills" = range(TA050050))
range_C2D <- TAS_original_data_new %>% select(TA050065) %>% drop_na() %>% summarize("Worry_about_expenses" = range(TA050065))
range_C2E <- TAS_original_data_new %>% select(TA050066) %>% drop_na() %>% summarize("Worry_about_future_job" = range(TA050066))
range_C2F <- TAS_original_data_new %>% select(TA050067) %>% drop_na() %>% filter(TA050067 <= 7) %>% summarize("Discouraged_about_future" = range(TA050067))
range_G1 <- TAS_original_data_new %>% select(TA050573) %>% drop_na() %>% filter(TA050573 < 3) %>% summarize("Education_status" = range(TA050573))
range_G2 <- TAS_original_data_new %>% select(TA050575) %>% drop_na() %>% filter(TA050575 > 0) %>% summarize("High_school_graduation_year" = range(TA050575))
range_G30A <- TAS_original_data_new %>% select(TA050639) %>% drop_na() %>% filter(TA050639 > 0) %>% summarize("Likelihood_of_well-paying_job" = range(TA050639))
range_G41A <- TAS_original_data_new %>% select(TA050663) %>% drop_na() %>% summarize("Importance_of_job_status" = range(TA050663))
range_G41B <- TAS_original_data_new %>% select(TA050664) %>% drop_na() %>% summarize("Importance_of_decision-making" = range(TA050664))
range_G41C <- TAS_original_data_new %>% select(TA050665) %>% drop_na() %>% summarize("Importance_of_challenging_work" = range(TA050665))
range_G41H <- TAS_original_data_new %>% select(TA050670) %>% drop_na() %>% summarize("Importance_of_healthcare_benefits" = range(TA050670))
range_G41P <- TAS_original_data_new %>% select(TA050675) %>% drop_na() %>% filter(TA050675 < 8) %>% summarize("Importance_of_job_central_to_identity" = range(TA050675))
range_H1 <- TAS_original_data_new %>% select(TA050676) %>% drop_na() %>% filter(TA050676 < 8) %>% summarize("General_health" = range(TA050676))
new_range <- data.frame(Name = c("Range_2005_low", "Range_2005_high"), range_B5A, range_B5D, range_B6C, range_C2D, range_C2E, range_C2F, range_G1, range_G2, range_G30A, range_G41A, range_G41B, range_G41C, range_G41H, range_G41P, range_H1)
TAS_descriptive_table_2005 <- rbind.data.frame(TAS_descriptive_table, new_range)
2005 TABLE
head(TAS_descriptive_table_2005)
## Name Responsibility_for_self Managing_own_money
## 1 Mean_2005 3.598658 4.3919463
## 2 SD_2005 1.163397 0.9329336
## 3 Range_2005_low 1.000000 1.0000000
## 4 Range_2005_high 5.000000 5.0000000
## Money_management_skills Worry_about_expenses Worry_about_future_job
## 1 5.348993 3.734228 3.620134
## 2 1.465216 1.897004 1.997141
## 3 1.000000 1.000000 1.000000
## 4 7.000000 7.000000 7.000000
## Discouraged_about_future Education_status High_school_graduation_year
## 1 3.074024 1.0710974 2003.724541
## 2 1.836633 0.2571863 1.066007
## 3 1.000000 1.0000000 2000.000000
## 4 7.000000 2.0000000 2005.000000
## Likelihood_of_well.paying_job Importance_of_job_status
## 1 5.998498 5.363758
## 2 1.019360 1.619945
## 3 1.000000 1.000000
## 4 7.000000 7.000000
## Importance_of_decision.making Importance_of_challenging_work
## 1 5.778523 5.520805
## 2 1.144444 1.186804
## 3 1.000000 1.000000
## 4 7.000000 7.000000
## Importance_of_healthcare_benefits Importance_of_job_central_to_identity
## 1 6.358389 5.070081
## 2 1.006237 1.543064
## 3 1.000000 1.000000
## 4 7.000000 7.000000
## General_health
## 1 2.1965007
## 2 0.9296776
## 3 1.0000000
## 4 5.0000000
knitr::kable(TAS_descriptive_table_2005)
| Mean_2005 |
3.598658 |
4.3919463 |
5.348993 |
3.734228 |
3.620134 |
3.074024 |
1.0710974 |
2003.724541 |
5.998499 |
5.363758 |
5.778524 |
5.520805 |
6.358389 |
5.070081 |
2.1965007 |
| SD_2005 |
1.163397 |
0.9329336 |
1.465216 |
1.897004 |
1.997141 |
1.836633 |
0.2571863 |
1.066007 |
1.019360 |
1.619945 |
1.144445 |
1.186804 |
1.006237 |
1.543064 |
0.9296776 |
| Range_2005_low |
1.000000 |
1.0000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.0000000 |
2000.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.0000000 |
| Range_2005_high |
5.000000 |
5.0000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
2.0000000 |
2005.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
5.0000000 |
2009
Mean
Mean_B5A_09 <- TAS_original_data_new %>% select(TA090045) %>% drop_na() %>% filter(TA090045 < 8) %>% summarize("Responsibility_for_self" = mean(TA090045))
Mean_B5D_09 <- TAS_original_data_new %>% select(TA090048) %>% drop_na() %>% filter(TA090048 < 8) %>% summarize("Managing_own_money" = mean(TA090048))
Mean_B6C_09 <- TAS_original_data_new %>% select(TA090051) %>% drop_na() %>% summarize("Money_management_skills" = mean(TA090051))
Mean_C2D_09 <- TAS_original_data_new %>% select(TA090066) %>% drop_na() %>% summarize("Worry_about_expenses" = mean(TA090066))
Mean_C2E_09 <- TAS_original_data_new %>% select(TA090067) %>% drop_na() %>% summarize("Worry_about_future_job" = mean(TA090067))
Mean_C2F_09 <- TAS_original_data_new %>% select(TA090068) %>% drop_na() %>% filter(TA090068 <= 7) %>% summarize("Discouraged_about_future" = mean(TA090068))
Mean_G1_09 <- TAS_original_data_new %>% select(TA090590) %>% drop_na() %>% filter(TA090590 > 0) %>% filter(TA090590 < 3) %>% summarize("Education_status" = mean(TA090590))
Mean_G2_09 <- TAS_original_data_new %>% select(TA090592) %>% drop_na() %>% filter(TA090592 > 0) %>% summarize("High_school_graduation_year" = mean(TA090592))
Mean_G30A_09 <- TAS_original_data_new %>% select(TA090663) %>% drop_na() %>% filter(TA090663 > 0) %>% filter(TA090663 < 9) %>% summarize("Likelihood_of_well-paying_job" = mean(TA090663))
Mean_G41A_09 <- TAS_original_data_new %>% select(TA090687) %>% drop_na() %>% filter(TA090687 < 8) %>% summarize("Importance_of_job_status" = mean(TA090687))
Mean_G41B_09 <- TAS_original_data_new %>% select(TA090688) %>% drop_na() %>% filter(TA090688 < 8) %>% summarize("Importance_of_decision-making" = mean(TA090688))
Mean_G41C_09 <- TAS_original_data_new %>% select(TA090689) %>% drop_na() %>% filter(TA090689 > 0) %>% filter(TA090689 < 8) %>% summarize("Importance_of_challenging_work" = mean(TA090689))
Mean_G41H_09 <- TAS_original_data_new %>% select(TA090694) %>% drop_na() %>% filter(TA090694 < 8) %>% summarize("Importance_of_healthcare_benefits" = mean(TA090694))
Mean_G41P_09 <- TAS_original_data_new %>% select(TA090699) %>% drop_na() %>% filter(TA090699 < 8) %>% summarize("Importance_of_job_central_to_identity" = mean(TA090699))
Mean_H1_09 <- TAS_original_data_new %>% select(TA090700) %>% drop_na() %>% filter(TA090700 < 8) %>% summarize("General_health" = mean(TA090700))
new_mean_09 <- data.frame(Name = c("Mean_2009"),Mean_B5A_09, Mean_B5D_09, Mean_B6C_09, Mean_C2D_09, Mean_C2E_09, Mean_C2F_09, Mean_G1_09, Mean_G2_09, Mean_G30A_09, Mean_G41A_09, Mean_G41B_09, Mean_G41C_09, Mean_G41H_09, Mean_G41P_09, Mean_H1_09)
TAS_descriptive_table_2005[nrow(TAS_descriptive_table_2005) + 1,] <- new_mean_09
2009
Standard Deviation
sd_B5A_09 <- TAS_original_data_new %>% select(TA090045) %>% drop_na() %>% filter(TA090045 < 8) %>% summarize(B5A = sd(TA090045))
sd_B5D_09 <- TAS_original_data_new %>% select(TA090048) %>% drop_na() %>% filter(TA090048 < 8) %>% summarize(B5D = sd(TA090048))
sd_B6C_09 <- TAS_original_data_new %>% select(TA090051) %>% drop_na() %>% summarize(B6C = sd(TA090051))
sd_C2D_09 <- TAS_original_data_new %>% select(TA090066) %>% drop_na() %>% summarize(C2D = sd(TA090066))
sd_C2E_09 <- TAS_original_data_new %>% select(TA090067) %>% drop_na() %>% summarize(C2E = sd(TA090067))
sd_C2F_09 <- TAS_original_data_new %>% select(TA090068) %>% drop_na() %>% filter(TA090068 <= 7) %>% summarize(C2F = sd(TA090068))
sd_G1_09 <- TAS_original_data_new %>% select(TA090590) %>% drop_na() %>% filter(TA090590 > 0) %>% filter(TA090590 < 3) %>% summarize(G1 = sd(TA090590))
sd_G2_09 <- TAS_original_data_new %>% select(TA090592) %>% drop_na() %>% filter(TA090592 > 0) %>% summarize(G2 = sd(TA090592))
sd_G30A_09 <- TAS_original_data_new %>% select(TA090663) %>% drop_na() %>% filter(TA090663 > 0) %>% filter(TA090663 < 9) %>% summarize(G30A = sd(TA090663))
sd_G41A_09 <- TAS_original_data_new %>% select(TA090687) %>% drop_na() %>% filter(TA090687 < 8) %>% summarize(G41A = sd(TA090687))
sd_G41B_09 <- TAS_original_data_new %>% select(TA090688) %>% drop_na() %>% filter(TA090688 < 8) %>% summarize(G41B = sd(TA090688))
sd_G41C_09 <- TAS_original_data_new %>% select(TA090689) %>% drop_na() %>% filter(TA090689 > 0) %>% filter(TA090689 < 8) %>% summarize(G41C = sd(TA090689))
sd_G41H_09 <- TAS_original_data_new %>% select(TA090694) %>% drop_na() %>% filter(TA090694 < 8) %>% summarize(G41H = sd(TA090694))
sd_G41P_09 <- TAS_original_data_new %>% select(TA090699) %>% drop_na() %>% filter(TA090699 < 8) %>% summarize(G41P = sd(TA090699))
sd_H1_09 <- TAS_original_data_new %>% select(TA090700) %>% drop_na() %>% filter(TA090700 < 8) %>% summarize(H1 = sd(TA090700))
new_sd_09 <- data.frame(Name = c("SD_2009"),sd_B5A_09, sd_B5D_09, sd_B6C_09, sd_C2D_09, sd_C2E_09, sd_C2F_09, sd_G1_09, sd_G2_09, sd_G30A_09, sd_G41A_09, sd_G41B_09, sd_G41C_09, sd_G41H_09, sd_G41P_09, sd_H1_09)
TAS_descriptive_table_2005[nrow(TAS_descriptive_table_2005) + 1,] <- new_sd_09
2009
Range
range_B5A_09 <- TAS_original_data_new %>% select(TA090045) %>% drop_na() %>% filter(TA090045 < 8) %>% summarize("Responsibility_for_self" = range(TA090045))
range_B5D_09 <- TAS_original_data_new %>% select(TA090048) %>% drop_na() %>% filter(TA090048 < 8) %>% summarize("Managing_own_money" = range(TA090048))
range_B6C_09 <- TAS_original_data_new %>% select(TA090051) %>% drop_na() %>% summarize("Money_management_skills" = range(TA090051))
range_C2D_09 <- TAS_original_data_new %>% select(TA090066) %>% drop_na() %>% summarize("Worry_about_expenses" = range(TA090066))
range_C2E_09 <- TAS_original_data_new %>% select(TA090067) %>% drop_na() %>% summarize("Worry_about_future_job" = range(TA090067))
range_C2F_09 <- TAS_original_data_new %>% select(TA090068) %>% drop_na() %>% filter(TA090068 <= 7) %>% summarize("Discouraged_about_future" = range(TA090068))
range_G1_09 <- TAS_original_data_new %>% select(TA090590) %>% drop_na() %>% filter(TA090590 > 0) %>% filter(TA090590 < 3) %>% summarize("Education_status" = range(TA090590))
range_G2_09 <- TAS_original_data_new %>% select(TA090592) %>% drop_na() %>% filter(TA090592 > 0) %>% summarize("High_school_graduation_year" = range(TA090592))
range_G30A_09 <- TAS_original_data_new %>% select(TA090663) %>% drop_na() %>% filter(TA090663 > 0) %>% filter(TA090663 < 9) %>% summarize("Likelihood_of_well-paying_job" = range(TA090663))
range_G41A_09 <- TAS_original_data_new %>% select(TA090687) %>% drop_na() %>% filter(TA090687 < 8) %>% summarize("Importance_of_job_status" = range(TA090687))
range_G41B_09 <- TAS_original_data_new %>% select(TA090688) %>% drop_na() %>% filter(TA090688 < 8) %>% summarize("Importance_of_decision-making" = range(TA090688))
range_G41C_09 <- TAS_original_data_new %>% select(TA090689) %>% drop_na() %>% filter(TA090689 > 0) %>% filter(TA090689 < 8) %>% summarize("Importance_of_challenging_work" = range(TA090689))
range_G41H_09 <- TAS_original_data_new %>% select(TA090694) %>% drop_na() %>% filter(TA090694 < 8) %>% summarize("Importance_of_healthcare_benefits" = range(TA090694))
range_G41P_09 <- TAS_original_data_new %>% select(TA090699) %>% drop_na() %>% filter(TA090699 < 8) %>% summarize("Importance_of_job_central_to_identity" = range(TA090699))
range_H1_09 <- TAS_original_data_new %>% select(TA090700) %>% drop_na() %>% filter(TA090700 < 8) %>% summarize("General_health" = range(TA090700))
new_range_09 <- data.frame(Name = c("Range_2009_low", "Range_2009_high"),range_B5A_09, range_B5D_09, range_B6C_09, range_C2D_09, range_C2E_09, range_C2F_09, range_G1_09, range_G2_09, range_G30A_09, range_G41A_09, range_G41B_09, range_G41C_09, range_G41H_09, range_G41P_09, range_H1_09)
TAS_descriptive_table_2009 <- rbind.data.frame(TAS_descriptive_table_2005, new_range_09)
2009 TABLE
head(TAS_descriptive_table_2009)
## Name Responsibility_for_self Managing_own_money
## 1 Mean_2005 3.598658 4.3919463
## 2 SD_2005 1.163397 0.9329336
## 3 Range_2005_low 1.000000 1.0000000
## 4 Range_2005_high 5.000000 5.0000000
## 5 Mean_2009 3.915593 4.5473278
## 6 SD_2009 1.154685 0.8715031
## Money_management_skills Worry_about_expenses Worry_about_future_job
## 1 5.348993 3.734228 3.620134
## 2 1.465216 1.897004 1.997141
## 3 1.000000 1.000000 1.000000
## 4 7.000000 7.000000 7.000000
## 5 5.456885 3.938867 3.771557
## 6 1.294799 1.915335 1.967525
## Discouraged_about_future Education_status High_school_graduation_year
## 1 3.074024 1.0710974 2003.724541
## 2 1.836633 0.2571863 1.066007
## 3 1.000000 1.0000000 2000.000000
## 4 7.000000 2.0000000 2005.000000
## 5 3.261261 1.0771429 2005.823256
## 6 1.799322 0.2669133 2.202281
## Likelihood_of_well.paying_job Importance_of_job_status
## 1 5.998498 5.363758
## 2 1.019360 1.619945
## 3 1.000000 1.000000
## 4 7.000000 7.000000
## 5 5.934321 4.961340
## 6 1.114947 1.799004
## Importance_of_decision.making Importance_of_challenging_work
## 1 5.778523 5.520805
## 2 1.144444 1.186804
## 3 1.000000 1.000000
## 4 7.000000 7.000000
## 5 5.694784 5.531230
## 6 1.230342 1.283503
## Importance_of_healthcare_benefits Importance_of_job_central_to_identity
## 1 6.358389 5.070081
## 2 1.006237 1.543064
## 3 1.000000 1.000000
## 4 7.000000 7.000000
## 5 6.327753 4.754522
## 6 1.093613 1.750560
## General_health
## 1 2.1965007
## 2 0.9296776
## 3 1.0000000
## 4 5.0000000
## 5 2.1867354
## 6 0.9066787
knitr::kable(TAS_descriptive_table_2009)
| Mean_2005 |
3.598658 |
4.3919463 |
5.348993 |
3.734228 |
3.620134 |
3.074024 |
1.0710974 |
2003.724541 |
5.998499 |
5.363758 |
5.778524 |
5.520805 |
6.358389 |
5.070081 |
2.1965007 |
| SD_2005 |
1.163397 |
0.9329336 |
1.465216 |
1.897004 |
1.997141 |
1.836633 |
0.2571863 |
1.066007 |
1.019360 |
1.619945 |
1.144445 |
1.186804 |
1.006237 |
1.543064 |
0.9296776 |
| Range_2005_low |
1.000000 |
1.0000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.0000000 |
2000.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.0000000 |
| Range_2005_high |
5.000000 |
5.0000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
2.0000000 |
2005.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
5.0000000 |
| Mean_2009 |
3.915593 |
4.5473278 |
5.456886 |
3.938867 |
3.771557 |
3.261261 |
1.0771429 |
2005.823256 |
5.934321 |
4.961340 |
5.694784 |
5.531230 |
6.327753 |
4.754522 |
2.1867354 |
| SD_2009 |
1.154684 |
0.8715031 |
1.294799 |
1.915335 |
1.967525 |
1.799322 |
0.2669133 |
2.202281 |
1.114947 |
1.799004 |
1.230342 |
1.283503 |
1.093613 |
1.750560 |
0.9066787 |
| Range_2009_low |
1.000000 |
1.0000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.0000000 |
1999.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.0000000 |
| Range_2009_high |
5.000000 |
5.0000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
2.0000000 |
2009.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
5.0000000 |
2015
Mean
Mean_B5A_15 <- TAS_original_data_new %>% select(TA150045) %>% drop_na() %>% filter(TA150045 < 8) %>% summarize("Responsibility_for_self" = mean(TA150045))
Mean_B5D_15 <- TAS_original_data_new %>% select(TA150048) %>% drop_na() %>% filter(TA150048 < 8) %>% summarize("Managing_own_money" = mean(TA150048))
Mean_B6C_15 <- TAS_original_data_new %>% select(TA150051) %>% drop_na() %>% summarize("Money_management_skills" = mean(TA150051))
Mean_C2D_15 <- TAS_original_data_new %>% select(TA150066) %>% drop_na() %>% summarize("Worry_about_expenses" = mean(TA150066))
Mean_C2E_15 <- TAS_original_data_new %>% select(TA150067) %>% drop_na() %>% summarize("Worry_about_future_job" = mean(TA150067))
Mean_C2F_15 <- TAS_original_data_new %>% select(TA150068) %>% drop_na() %>% filter(TA150068 <= 7) %>% summarize("Discouraged_about_future" = mean(TA150068))
Mean_G1_15 <- TAS_original_data_new %>% select(TA150701) %>% drop_na() %>% filter(TA150701 > 0) %>% filter(TA150701 < 3) %>% summarize("Education_status" = mean(TA150701))
Mean_G2_15 <- TAS_original_data_new %>% select(TA150703) %>% drop_na() %>% filter(TA150703 > 0) %>% summarize("High_school_graduation_year" = mean(TA150703))
Mean_G30A_15 <- TAS_original_data_new %>% select(TA150784) %>% drop_na() %>% filter(TA150784 > 0) %>% filter(TA150784 < 9) %>% summarize("Likelihood_of_well-paying_job" = mean(TA150784))
Mean_G41A_15 <- TAS_original_data_new %>% select(TA150808) %>% drop_na() %>% filter(TA150808 < 8) %>% summarize("Importance_of_job_status" = mean(TA150808))
Mean_G41B_15 <- TAS_original_data_new %>% select(TA150809) %>% drop_na() %>% filter(TA150809 < 8) %>% summarize("Importance_of_decision-making" = mean(TA150809))
Mean_G41C_15 <- TAS_original_data_new %>% select(TA150810) %>% drop_na() %>% filter(TA150810 > 0) %>% filter(TA150810 < 8) %>% summarize("Importance_of_challenging_work" = mean(TA150810))
Mean_G41H_15 <- TAS_original_data_new %>% select(TA150815) %>% drop_na() %>% filter(TA150815 < 8) %>% summarize("Importance_of_healthcare_benefits" = mean(TA150815))
Mean_G41P_15 <- TAS_original_data_new %>% select(TA150820) %>% drop_na() %>% filter(TA150820 < 8) %>% summarize("Importance_of_job_central_to_identity" = mean(TA150820))
Mean_H1_15 <- TAS_original_data_new %>% select(TA150821) %>% drop_na() %>% filter(TA150821 < 8) %>% summarize("General_health" = mean(TA150821))
new_mean_15 <- data.frame(Name = c("Mean_2015"),Mean_B5A_15, Mean_B5D_15, Mean_B6C_15, Mean_C2D_15, Mean_C2E_15, Mean_C2F_15, Mean_G1_15, Mean_G2_15, Mean_G30A_15, Mean_G41A_15, Mean_G41B_15, Mean_G41C_15, Mean_G41H_15, Mean_G41P_15, Mean_H1_15)
TAS_descriptive_table_2009[nrow(TAS_descriptive_table_2009) + 1,] <- new_mean_15
2015
Standard Deviation
sd_B5A_15 <- TAS_original_data_new %>% select(TA150045) %>% drop_na() %>% filter(TA150045 < 8) %>% summarize(B5A = sd(TA150045))
sd_B5D_15 <- TAS_original_data_new %>% select(TA150048) %>% drop_na() %>% filter(TA150048 < 8) %>% summarize(B5D = sd(TA150048))
sd_B6C_15 <- TAS_original_data_new %>% select(TA150051) %>% drop_na() %>% summarize(B6C = sd(TA150051))
sd_C2D_15 <- TAS_original_data_new %>% select(TA150066) %>% drop_na() %>% summarize(C2D = sd(TA150066))
sd_C2E_15 <- TAS_original_data_new %>% select(TA150067) %>% drop_na() %>% summarize(C2E = sd(TA150067))
sd_C2F_15 <- TAS_original_data_new %>% select(TA150068) %>% drop_na() %>% filter(TA150068 <= 7) %>% summarize(C2F = sd(TA150068))
sd_G1_15 <- TAS_original_data_new %>% select(TA150701) %>% drop_na() %>% filter(TA150701 > 0) %>% filter(TA150701 < 3) %>% summarize(G1 = sd(TA150701))
sd_G2_15 <- TAS_original_data_new %>% select(TA150703) %>% drop_na() %>% filter(TA150703 > 0) %>% summarize(G2 = sd(TA150703))
sd_G30A_15 <- TAS_original_data_new %>% select(TA150784) %>% drop_na() %>% filter(TA150784 > 0) %>% filter(TA150784 < 9) %>% summarize(G30A = sd(TA150784))
sd_G41A_15 <- TAS_original_data_new %>% select(TA150808) %>% drop_na() %>% filter(TA150808 < 8) %>% summarize(G41A = sd(TA150808))
sd_G41B_15 <- TAS_original_data_new %>% select(TA150809) %>% drop_na() %>% filter(TA150809 < 8) %>% summarize(G41B = sd(TA150809))
sd_G41C_15 <- TAS_original_data_new %>% select(TA150810) %>% drop_na() %>% filter(TA150810 > 0) %>% filter(TA150810 < 8) %>% summarize(G41C = sd(TA150810))
sd_G41H_15 <- TAS_original_data_new %>% select(TA150815) %>% drop_na() %>% filter(TA150815 < 8) %>% summarize(G41H = sd(TA150815))
sd_G41P_15 <- TAS_original_data_new %>% select(TA150820) %>% drop_na() %>% filter(TA150820 < 8) %>% summarize(G41P = sd(TA150820))
sd_H1_15 <- TAS_original_data_new %>% select(TA150821) %>% drop_na() %>% filter(TA150821 < 8) %>% summarize(H1 = sd(TA150821))
new_sd_15 <- data.frame(Name = c("SD_2015"),sd_B5A_15, sd_B5D_15, sd_B6C_15, sd_C2D_15, sd_C2E_15, sd_C2F_15, sd_G1_15, sd_G2_15, sd_G30A_15, sd_G41A_15, sd_G41B_15, sd_G41C_15, sd_G41H_15, sd_G41P_15, sd_H1_15)
TAS_descriptive_table_2009[nrow(TAS_descriptive_table_2009) + 1,] <- new_sd_15
2015
Range
range_B5A_15 <- TAS_original_data_new %>% select(TA150045) %>% drop_na() %>% filter(TA150045 < 8) %>% summarize("Responsibility_for_self" = range(TA150045))
range_B5D_15 <- TAS_original_data_new %>% select(TA150048) %>% drop_na() %>% filter(TA150048 < 8) %>% summarize("Managing_own_money" = range(TA150048))
range_B6C_15 <- TAS_original_data_new %>% select(TA150051) %>% drop_na() %>% summarize("Money_management_skills" = range(TA150051))
range_C2D_15 <- TAS_original_data_new %>% select(TA150066) %>% drop_na() %>% summarize("Worry_about_expenses" = range(TA150066))
range_C2E_15 <- TAS_original_data_new %>% select(TA150067) %>% drop_na() %>% summarize("Worry_about_future_job" = range(TA150067))
range_C2F_15 <- TAS_original_data_new %>% select(TA150068) %>% drop_na() %>% filter(TA150068 <= 7) %>% summarize("Discouraged_about_future" = range(TA150068))
range_G1_15 <- TAS_original_data_new %>% select(TA150701) %>% drop_na() %>% filter(TA150701 > 0) %>% filter(TA150701 < 3) %>% summarize("Education_status" = range(TA150701))
range_G2_15 <- TAS_original_data_new %>% select(TA150703) %>% drop_na() %>% filter(TA150703 > 0) %>% summarize("High_school_graduation_year" = range(TA150703))
range_G30A_15 <- TAS_original_data_new %>% select(TA150784) %>% drop_na() %>% filter(TA150784 > 0) %>% filter(TA150784 < 9) %>% summarize("Likelihood_of_well-paying_job" = range(TA150784))
range_G41A_15 <- TAS_original_data_new %>% select(TA150808) %>% drop_na() %>% filter(TA150808 < 8) %>% summarize("Importance_of_job_status" = range(TA150808))
range_G41B_15 <- TAS_original_data_new %>% select(TA150809) %>% drop_na() %>% filter(TA150809 < 8) %>% summarize("Importance_of_decision-making" = range(TA150809))
range_G41C_15 <- TAS_original_data_new %>% select(TA150810) %>% drop_na() %>% filter(TA150810 > 0) %>% filter(TA150810 < 8) %>% summarize("Importance_of_challenging_work" = range(TA150810))
range_G41H_15 <- TAS_original_data_new %>% select(TA150815) %>% drop_na() %>% filter(TA150815 < 8) %>% summarize("Importance_of_healthcare_benefits" = range(TA150815))
range_G41P_15 <- TAS_original_data_new %>% select(TA150820) %>% drop_na() %>% filter(TA150820 < 8) %>% summarize("Importance_of_job_central_to_identity" = range(TA150820))
range_H1_15 <- TAS_original_data_new %>% select(TA150821) %>% drop_na() %>% filter(TA150821 < 8) %>% summarize("General_health" = range(TA150821))
new_range_15 <- data.frame(Name = c("Range_2015_low", "Range_2015_high"),range_B5A_15, range_B5D_15, range_B6C_15, range_C2D_15, range_C2E_15, range_C2F_15, range_G1_15, range_G2_15, range_G30A_15, range_G41A_15, range_G41B_15, range_G41C_15, range_G41H_15, range_G41P_15, range_H1_15)
final_TAS_descriptive_table <- rbind.data.frame(TAS_descriptive_table_2009, new_range_15)
Step 5: TAS descriptive statistics table
head(final_TAS_descriptive_table)
## Name Responsibility_for_self Managing_own_money
## 1 Mean_2005 3.598658 4.3919463
## 2 SD_2005 1.163397 0.9329336
## 3 Range_2005_low 1.000000 1.0000000
## 4 Range_2005_high 5.000000 5.0000000
## 5 Mean_2009 3.915593 4.5473278
## 6 SD_2009 1.154685 0.8715031
## Money_management_skills Worry_about_expenses Worry_about_future_job
## 1 5.348993 3.734228 3.620134
## 2 1.465216 1.897004 1.997141
## 3 1.000000 1.000000 1.000000
## 4 7.000000 7.000000 7.000000
## 5 5.456885 3.938867 3.771557
## 6 1.294799 1.915335 1.967525
## Discouraged_about_future Education_status High_school_graduation_year
## 1 3.074024 1.0710974 2003.724541
## 2 1.836633 0.2571863 1.066007
## 3 1.000000 1.0000000 2000.000000
## 4 7.000000 2.0000000 2005.000000
## 5 3.261261 1.0771429 2005.823256
## 6 1.799322 0.2669133 2.202281
## Likelihood_of_well.paying_job Importance_of_job_status
## 1 5.998498 5.363758
## 2 1.019360 1.619945
## 3 1.000000 1.000000
## 4 7.000000 7.000000
## 5 5.934321 4.961340
## 6 1.114947 1.799004
## Importance_of_decision.making Importance_of_challenging_work
## 1 5.778523 5.520805
## 2 1.144444 1.186804
## 3 1.000000 1.000000
## 4 7.000000 7.000000
## 5 5.694784 5.531230
## 6 1.230342 1.283503
## Importance_of_healthcare_benefits Importance_of_job_central_to_identity
## 1 6.358389 5.070081
## 2 1.006237 1.543064
## 3 1.000000 1.000000
## 4 7.000000 7.000000
## 5 6.327753 4.754522
## 6 1.093613 1.750560
## General_health
## 1 2.1965007
## 2 0.9296776
## 3 1.0000000
## 4 5.0000000
## 5 2.1867354
## 6 0.9066787
knitr::kable(final_TAS_descriptive_table)
| Mean_2005 |
3.598658 |
4.3919463 |
5.348993 |
3.734228 |
3.620134 |
3.074024 |
1.0710974 |
2003.724541 |
5.998499 |
5.363758 |
5.778524 |
5.520805 |
6.358389 |
5.070081 |
2.1965007 |
| SD_2005 |
1.163397 |
0.9329336 |
1.465216 |
1.897004 |
1.997141 |
1.836633 |
0.2571863 |
1.066007 |
1.019360 |
1.619945 |
1.144445 |
1.186804 |
1.006237 |
1.543064 |
0.9296776 |
| Range_2005_low |
1.000000 |
1.0000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.0000000 |
2000.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.0000000 |
| Range_2005_high |
5.000000 |
5.0000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
2.0000000 |
2005.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
5.0000000 |
| Mean_2009 |
3.915593 |
4.5473278 |
5.456886 |
3.938867 |
3.771557 |
3.261261 |
1.0771429 |
2005.823256 |
5.934321 |
4.961340 |
5.694784 |
5.531230 |
6.327753 |
4.754522 |
2.1867354 |
| SD_2009 |
1.154684 |
0.8715031 |
1.294799 |
1.915335 |
1.967525 |
1.799322 |
0.2669133 |
2.202281 |
1.114947 |
1.799004 |
1.230342 |
1.283503 |
1.093613 |
1.750560 |
0.9066787 |
| Range_2009_low |
1.000000 |
1.0000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.0000000 |
1999.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.0000000 |
| Range_2009_high |
5.000000 |
5.0000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
2.0000000 |
2009.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
5.0000000 |
| Mean_2015 |
4.081197 |
4.5997559 |
5.426569 |
3.607556 |
3.495430 |
3.086533 |
1.0611046 |
2011.609130 |
6.040268 |
4.809030 |
5.596705 |
5.489903 |
6.178768 |
4.936430 |
2.2971324 |
| SD_2015 |
1.122383 |
0.8369664 |
1.286753 |
1.888551 |
1.954079 |
1.783343 |
0.2396629 |
2.536843 |
1.085295 |
1.861706 |
1.359276 |
1.286893 |
1.227638 |
1.666983 |
0.9448454 |
| Range_2015_low |
1.000000 |
1.0000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.0000000 |
2001.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.000000 |
1.0000000 |
| Range_2015_high |
5.000000 |
5.0000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
2.0000000 |
2015.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
7.000000 |
5.0000000 |