Z and T tables and Excel functions for two-tailed cases
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Using tables and Excel normal and t distribution functions for confidence intervals and two-tailed hypothesis testing
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Standard normal distribution
Student's t-distribution
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confidence level =
99.0%
confidence level =
99.0%
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conf coefficient = 1-alpha =
0.990
i.e. this is the area inside the two tails
conf coefficient = 1-alpha =
0.990
i.e. this is the area inside the two tails
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alpha =0.010
i.e. this is the total area outside the two tails
alpha =0.010
i.e. this is the area outside the two tails
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alpha / 2 =0.005
i.e. this is the area to the right of z
alpha / 2 =0.005
i.e. this is the area to the right of t
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area for Kvanli =
0.495
i.e. Kvanli Z table table expects 0.5000 - alpha/2 *
area for Kvanli =
0.005
i.e. Kvanli T table expects area to the right of t *
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area for Walpole =
0.995
i.e. Walpole table expects 1.0000 - alpha/2 *
area for Walpole =
0.005
i.e. Walpole T table expects area to the right of t *
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n =41
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df = n-1 =40
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prob for NORMSINV(prob) and NORMS.S.INV(prob) =
0.995
i.e. these functions expect prob to be area to the left of z-score = 1.0000 - alpha/2
prob for TINV(prob, df) =
0.010
i.e. this is the two-tailed function and expects prob to be both areas in the tails = alpha
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NORMSINV(prob) =
2.575829306
TINV(prob, df) =
2.7044593
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NORM.S.INV(prob) =
2.575829306
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TDIST(t, df, tails) = TDIST(t, df, 2) =
0.01
i.e. this function returns the total area outside the tails if called for 2 tails
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NORMSDIST(z) =
0.995
i.e. this function gives the area to the left of the z-score
TDIST(t, df, tails) = TDIST(t, df, 1) =
0.005
i.e. this function returns the area the right of t if called for 1 tail
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prob for T.INV(prob, df) =
0.995
i.e. this is a one-tailed function and expects prob to be area to the left of t, i.e. 1.000 - alpha / 2
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T.INV(prob, df) =
2.7044593
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Note that the functions shown in the video but not here are not part of Google Spreadsheets
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*
Note that the printed tables don't give values for all possible confidence levels
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