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Confidence Intervals, Hypothesis Testings, and finding Sample size for 1-Sample Data


  • Code to find Confidence Interval for 1-sample population mean when data are given and population standard deviation sigma is not known.

  • Code to find Confidence Interval for 1-sample population mean when data are given and population standard deviation sigma is given.
    • Input: Data x; Population standard deviation sigma; Confidence Level CL (in percentage without percentage symbol).
    • CI_Data_For_Mue_With_Sigma.R

  • Code to find Confidence Interval for 1-sample population mean when data are not given and population standard deviation sigma is not known.
    • Input: Sample size n; Sample mean x_bar; Sample standard deviation s; Confidence Level CL (in percentage without percentage symbol).
    • CI_For_Mue_No_Sigma.R

  • Code to find Confidence Interval for 1-sample population mean when data are not given and population standard deviation sigma is known.
    • Input: Sample size n; Sample mean x_bar; Population standard deviation sigma; Confidence Level CL (in percentage without percentage symbol).
    • CI_For_Mue_With_Sigma.R

  • Code to find Confidence Interval for 1-sample population proportion.
    • Input: Number of subjects who falls in the category of interest x; sample size n; Confidence level CL (in percentage without percentage symbol).
    • CI_For_p.R
  • Code to find Confidence Interval for 1-sample population standard deviation and variance when data are not given.
    • Input: Sample size n; Sample standard deviation s; Confidence Level CL (in percentage without percentage symbol).
    • CI_For_Variance.R

  • Code to carryout Hypothesis Testing for 1-sample population mean when data are given and population standard deviation sigma is not known.
    • Input: Data x; Null hypothesis population mean mue0; Alternative hypothesis H1 ('less', 'greater', or 'two.sided') ; Level of significance alpha.
    • HT_Data_For_Mue_No_Sigma.R

  • Code to carryout Hypothesis Testing for 1-sample population mean when data are given and population standard deviation sigma is not known.
    • Input: Data x; Null hypothesis population mean mue0; Alternative hypothesis H1 ('less', 'greater', or 'two.sided'); Level of significance alpha.
    • HT_Data_For_Mue_With_Sigma.R

  • Code to carryout Hypothesis Testing for 1-sample population variance and standard deviation when data are given.
    • Input: Data x; Null hypothesis population standard deviation sigma0; Alternative hypothesis H1 ('less', 'greater', or 'two.sided'); Level of significance alpha.
    • HT_Data_For_Variance.R

  • Code to carryout Hypothesis Testing for 1-Sample population mean when data are not given and population standard deviation sigma is not given.
    • Input: Sample size n; Sample mean x_bar; Null hypothesis mean mue0; Sample standard deviation s; Alternative hypothesis H1 ('less', 'greater', or 'two.sided'); Level of significance alpha.
    • HT_For_Mue_No_Sigma.R

  • Code to carryout Hypothesis Testing for 1-Sample population mean when data are not given and population standard deviation sigma is given.
    • Input: Sample size n; Sample mean x_bar; Null hypothesis mean mue0; Population standard deviation sigma; Alternative hypothesis H1 ('less', 'greater', or 'two.sided'); Level of significance alpha.
    • HT_For_Mue_With_Sigma.R

  • Code to carryout Hypothesis Testing for 1-Sample population proportion when sample size is very small.
    • Input: Number of subjects who falls in the category of interest x; sample size n; Null hypothesis proportion p0; Alternative hypothesis H1 ('less', 'greater', or 'two.sided').
    • HT_For_p_Binom.R

  • Code to carryout Hypothesis Testing for 1-Sample population proportion when sample size is large.
    • Input: Number of subjects who falls in the category of interest x; sample size n; Null hypothesis proportion p0; Alternative hypothesis H1 ('less', 'greater', or 'two.sided'); Level of significance alpha.
    • HT_For_p_Normal.R

  • Code to carryout Hypothesis Testing for 1-sample population variance and standard deviation when data are not given.
    • Input: Sample size n; Sample standard deviation s; Null hypothesis standard deviation sigma0; Alternative hypothesis H1 ('less', 'greater', or 'two.sided'); Level of significance alpha.
    • HT_For_Variance.R

  • Code to find Confidence Interval for 1-sample population standard deviation and variance when data are given.

  • Code to find sample size for categorical data using the margin of error.
    • Input: Sample proportion pHat; Confidence level CL (in percentage without percentage symbol); Margin of error E (in decimal)
    • Sample_Size_Categorical.R

  • Code to find sample size for quantitative data using the margin of error and population standard deviation.
    • Input: Population standard deviation sigma; Confidence Level CL (in percentage without percentage symbol); Margin of error E
    • Sample_Size_Quantitative.R



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